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At least 1,045 records · Page 58

An Efficient Objective Analysis System for Parallel Computers

A new atmospheric objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 1 X 1 lat-lon grid with 18 levels of heights and winds and 10 levels of moisture) using 120,000 observations in 17 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system is totally portable and can run on several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from 1 to 32 CPUs is 18%. In addition, the analysis results are identical regardless of the number of processors used. This system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. Static tests with a 2 X 2.5 resolution version of this system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from several months of cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (O-F statistics) as the current operational system.

Stobie, J.↗

An Efficient Objective Analysis System for Parallel Computers

A new objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 2 x 2.5 lat-lon grid with 20 levels of heights and winds and 10 levels of moisture) using 120,000 observations in less than 3 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system Ls totally portable and can run on -several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from I to 32 CPus is 18%. in addition, the analysis results are identical regardless of the number of processors used. T'his system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. It also includes a new quality control (buddy check) system. Static tests with the system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from a 2-month cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (0-F statistics) throughout the entire two months.

Stobie, James G.↗

Preliminary Operational Results of the TDRSS Onboard Navigation System (TONS) for the Terra Mission

The Earth Observing System Terra spacecraft was launched on December 18, 1999, to provide data for the characterization of the terrestrial and oceanic surfaces, clouds, radiation, aerosols, and radiative balance. The Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (ONS) (TONS) flying on Terra provides the spacecraft with an operational real-time navigation solution. TONS is a passive system that makes judicious use of Terra's communication and computer subsystems. An objective of the ONS developed by NASA's Goddard Space Flight Center (GSFC) Guidance, Navigation and Control Center is to provide autonomous navigation with minimal power, weight, and volume impact on the user spacecraft. TONS relies on extracting tracking measurements onboard from a TDRSS forward-link communication signal and processing these measurements in an onboard extended Kalman filter to estimate Terra's current state. Terra is the first NASA low Earth orbiting mission to fly autonomous navigation which produces accurate results. The science orbital accuracy requirements for Terra are 150 meters (m) (3sigma) per axis with a goal of 5m (1 sigma) RSS which TONS is expected to meet. The TONS solutions are telemetered in real-time to the mission scientists along with their science data for immediate processing. Once set in the operational mode, TONS eliminates the need for ground orbit determination and allows for a smooth flow from the spacecraft telemetry to planning products for the mission team. This paper will present the preliminary results of the operational TONS solution available from Terra.

Gramling, Cheryl↗

Inorganic Chlorine Partitioning in the Summer Lower Stratosphere: Modeled and Measured [ClONO2/HCl] During POLARIS

We examine inorganic chlorine (Cly) partitioning in the summer lower stratosphere using in situ ER-2 aircraft observations made during the Photochemistry of Ozone Loss in the Arctic Region in Summer (POLARIS) campaign. New steady state and numerical models estimate [ClONO2]/[HCl] using currently accepted photochemistry. These models are tightly constrained by observations with OH (parameterized as a function of solar zenith angle) substituting for modeled HO2 chemistry. We find that inorganic chlorine photochemistry alone overestimates observed [ClONO2]/[HCl] by approximately 55-60% at mid and high latitudes. On the basis of POLARIS studies of the inorganic chlorine budget, [ClO]/[ClONO2], and an intercomparison with balloon observations, the most direct explanation for the model-measurement discrepancy in Cly partitioning is an error in the reactions, rate constants, and measured species concentrations linking HCl and ClO (simulated [ClO]/[HCl] too high) in combination with a possible systematic error in the ER-2 ClONO2 measurement (too low). The high precision of our simulation (+/-15% 1-sigma for [ClONO2]/[HCl], which is compared with observations) increases confidence in the observations, photolysis calculations, and laboratory rate constants. These results, along with other findings, should lead to improvements in both the accuracy and precision of stratospheric photochemical models.

Voss, P. B.↗

Detection of Urban-Induced Rainfall Anomalies in Houston, Texas: A New Perspective from Space

Urban heat islands (UHIs) are caused by the heat-retaining properties of surfaces usually found in urban cities like asphalt and concrete. The UHI can typically be observed on the evening TV weather map as warmer temperatures over the downtown of major cities and cooler temperatures in the suburbs and surrounding rural areas. The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad environmental and societal implications. Interest in the UHI will intensify in the future as existing urban areas expand and rural areas urbanize. By the year 2025, more than 60% of the world's population will live in cities, with higher percentages expected in developed nations. The urban growth rate in the United States, for example, is estimated to be 12.5%, and the recent 2000 Census found that more than 80% of the population currently lives in urban areas. Furthermore, the U.S. population is not only growing but is tending to concentrate more in urban areas within the environmentally sensitive coastal zones. Urban growth creates unique and often contentious issues for policymakers related to land use zoning, transportation planning, agricultural production, housing and development, pollution, and natural resources protection. Urban expansion and its associated UHIs also have measurable impacts on weather and climate processes. The UHI has been documented to affect local and regional temperature, wind patterns, and air quality.

Shepherd, J. Marshall↗

Detection of Urban-Induced Rainfall Anomalies in a Major Coastal City

Urban heat islands (UHIs) are caused by the heat-retaining properties of surfaces usually found in urban cities like asphalt and concrete. The UHI can typically be observed on the evening TV weather map as warmer temperatures over the downtown of major cities and cooler temperatures in the suburbs and surrounding rural areas. The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad environmental and societal implications. Interest in the UHI will intensify in the future as existing urban areas expand and rural areas urbanize. By the year 2025, more than 60% of the world s population will live in cities, with higher percentages expected in developed nations. The urban growth rate in the United States, for example, is estimated to be 12.5%, and the recent 2000 Census found that more than 80% of the population currently lives in urban areas. Furthermore, the U.S. population is not only growing but is tending to concentrate more in urban areas within the environmentally sensitive coastal zones. Urban growth creates unique and often contentious issues for policymakers related to land use zoning, transportation planning, agricultural production, housing and development, pollution, and natural resources protection. Urban expansion and its associated TJHIs also have measurable impacts on weather and climate processes. The UHI has been documented to affect local and regional temperature, wind patterns, and air quality

Shepherd, J. Marshall↗

The Reanalysis for Stratospheric Trace-gas Studies

In order to re-examine trace gas transport in the middle atmosphere for the period May 1991 until April 1995, a "reanalysis" is being performed using an up-to-date version of the DAO's "GEOS" assimilation system. The Reanalysis for Stratospheric Trace-gas Studies (ReSTS) is intended to provide state-of-the-art estimates of the atmosphere during a period when the Upper Atmospheric Research Satellite provided a high density of trace-gas observations, and when the aerosol loading from the eruption of Mount Pinatubo contaminated the lower stratosphere, at the same time performing a natural tracer transport experiment. This study will present the first results from ReSTS, focussing on the improvements over the meteorological analyses produced by the then-operational GEOS-1 data assimilation system; emphasis will be placed on the improved representations of physical processes between GEOS-1 and the current GEOS-4 systems, highlighting the transport properties of the datasets. Alongside the production of a comprehensive atmospheric dataset, important components of ReSTS include performing sensitivity studies to the formulation of the assimilation system (including the representation of physical processes in the GCM, such as feedbacks between ozone/aerosols and meteorology) and to the inclusion of additional data types (including limb-sounding temperature data alongside the TOVS observations). Impacts of some of these factors on the analyzed meteorology and transport will be discussed. Of particular interest are attempts to determine the relative importance of various steps in the assimilation process to the quality of the final analyses.

Pawson, Steven↗

General Multimechanism Reversible-Irreversible Time-Dependent Constitutive Deformation Model Being Developed

Since most advanced material systems (for example metallic-, polymer-, and ceramic-based systems) being currently researched and evaluated are for high-temperature airframe and propulsion system applications, the required constitutive models must account for both reversible and irreversible time-dependent deformations. Furthermore, since an integral part of continuum-based computational methodologies (be they microscale- or macroscale-based) is an accurate and computationally efficient constitutive model to describe the deformation behavior of the materials of interest, extensive research efforts have been made over the years on the phenomenological representations of constitutive material behavior in the inelastic analysis of structures. From a more recent and comprehensive perspective, the NASA Glenn Research Center in conjunction with the University of Akron has emphasized concurrently addressing three important and related areas: that is, 1) Mathematical formulation; 2) Algorithmic developments for updating (integrating) the external (e.g., stress) and internal state variables; 3) Parameter estimation for characterizing the model. This concurrent perspective to constitutive modeling has enabled the overcoming of the two major obstacles to fully utilizing these sophisticated time-dependent (hereditary) constitutive models in practical engineering analysis. These obstacles are: 1) Lack of efficient and robust integration algorithms; 2) Difficulties associated with characterizing the large number of required material parameters, particularly when many of these parameters lack obvious or direct physical interpretations.

Saleeb, A. F.↗

Retrieval of Soil Moisture Profile by Combined Remote Sensing and Modeling

The objective of this paper is to develop a statistically optimal assimilation algorithm which estimates the entire system state, i.e., vertical soil moisture and temperature profiles, from information which is only available for portion of the system (namely, the near-surface soil moisture and temperature).

soil moisture profiles↗

Magnetospheric Multiscale (MMS) Mission Commissioning Phase Orbit Determination Error Analysis

The Magnetospheric MultiScale (MMS) mission commissioning phase starts in a 185 km altitude x 12 Earth radii (RE) injection orbit and lasts until the Phase 1 mission orbits and orientation to the Earth-Sun li ne are achieved. During a limited time period in the early part of co mmissioning, five maneuvers are performed to raise the perigee radius to 1.2 R E, with a maneuver every other apogee. The current baseline is for the Goddard Space Flight Center Flight Dynamics Facility to p rovide MMS orbit determination support during the early commissioning phase using all available two-way range and Doppler tracking from bo th the Deep Space Network and Space Network. This paper summarizes th e results from a linear covariance analysis to determine the type and amount of tracking data required to accurately estimate the spacecraf t state, plan each perigee raising maneuver, and support thruster cal ibration during this phase. The primary focus of this study is the na vigation accuracy required to plan the first and the final perigee ra ising maneuvers. Absolute and relative position and velocity error hi stories are generated for all cases and summarized in terms of the ma ximum root-sum-square consider and measurement noise error contributi ons over the definitive and predictive arcs and at discrete times inc luding the maneuver planning and execution times. Details of the meth odology, orbital characteristics, maneuver timeline, error models, and error sensitivities are provided.

Chung, Lauren R.↗

Emission Spectroscopic Measurements in the Plenum Region of the NASA IHF Arc Jet Facility

A newly designed segment with optical access was installed in the plenum chamber of the 60 MW Interaction Heating arcjet Facility at NASA Ames Research Center. This special segment has ports located off axis, and the optical fibers can be inserted into these ports. The special segment allows for optical examination of the arc-heated flow as it enters the plenum, and thus assists in determining estimates of the thermodynamic state of the inflow to the convergent section of the nozzle. In the present work, optical emission measurements have been made in VIS-NIR region (wavelengths between 500 nm to 900 nm) for two settings of the arc heater - a 6000 A condition (high condition) with the minimum amount of radial injection of cold air in the plenum, and a 3300 A condition (low condition) with significant amount of cold air injection to reduce the enthalpy of the arc-heated stream. The results presented here were obtained using an Acton SP300i spectrometer coupled to a Princeton Instruments PI-max intensified camera. In addition to the optical emission measurements, computations were performed for the flow in the plenum and radiation along lines of sight corresponding to the optical ports. Along the centerline, i.e., the longest line of sight across the plenum cross-section, there is good agreement between computations and measurements for the high enthalpy condition, although the off-axis radial profiles show some differences. For the low enthalpy condition, there are significant differences between computations and measurements. The current working hypothesis is that the computational model does not capture details of the mixing process in the plenum.

Winter, Michael W.↗

Decentralized Adaptive Control of Systems with Uncertain Interconnections, Plant-Model Mismatch and Actuator Failures

Decentralized adaptive control is considered for systems consisting of multiple interconnected subsystems. It is assumed that each subsystem s parameters are uncertain and the interconnection parameters are not known. In addition, mismatch can exist between each subsystem and its reference model. A strictly decentralized adaptive control scheme is developed, wherein each subsystem has access only to its own state but has the knowledge of all reference model states. The mismatch is estimated online for each subsystem and the mismatch estimates are used to adaptively modify the corresponding reference models. The adaptive control scheme is extended to the case with actuator failures in addition to mismatch.

Patre, Parag↗

Quantifying the Aerosol Semi-Direct Effect in the NASA GEOS-5 AGCM

Aerosols such as black carbon, dust, and some organic carbon species both scatter and absorb incoming solar radiation. This direct aerosol radiative forcing (DARF) redistributes solar energy both by cooling the surface and warming the atmosphere. As a result, these aerosols affect atmospheric stability and cloud cover (the semi-direct effect, or SDE). Furthermore, in regions with persistent high loadings of absorbing aerosols (e.g. Asia), regional circulation patterns may be altered, potentially resulting in changes in precipitation patterns. Here we investigate aerosol-climate coupling using the NASA Goddard Earth Observing System model version 5 (GEOS-5) atmospheric general circulation model (AGCM), in which we have implemented an online version of the Goddard Chemistry, Aerosol, Radiation and Transport (GOCART) model. GOCART includes representations of the sources, sinks, and chemical transformation of externally mixed dust, sea salt, sulfate, and carbonaceous aerosols. We examine a series of free-running ensemble climate simulations of the present-day period (2000-2009) forced by observed sea surface temperatures to determine the impact of aerosols on the model climate. The SDE and response of each simulation is determined by differencing with respect to the control simulation (no aerosol forcing). In a free-running model, any estimate of the SDE includes changes in clouds due both to atmospheric heating from aerosols and changes in circulation. To try and quantify the SDE without these circulation changes we then examine the DARF and SDE in GEOS-5 with prescribed meteorological analyses introduced by the MERRA analysis. By doing so, we are able to examine changes in model clouds that occur on shorter scales (six hours). In the GEOS-5 data assimilation system (DAS), the analysis is defined as the best estimate of the atmospheric state at any given time, and it is determined by optimally combining a first-guess short-term GCM forecast with all available observations. The Incremental Analysis Update (IAU) is added to the model forecast tendencies to align them with the analysis every six hours, thus preventing longer timescale feedbacks due to the aerosol forcing. We calculate the SDE by comparing model runs with and without aerosols, and the difference in the IAU between these runs is a useful metric with which to evaluate the impact of the SDE on the model atmosphere and clouds. Decreasing the IAU indicates that the aerosol direct and semi-direct effects act to reduce the bias between the model and observations and vice versa.

Randles, Cynthia A.↗

Heat Transfer Modeling for Rigid High-Temperature Fibrous Insulation

Combined radiation and conduction heat transfer through a high-temperature, high-porosity, rigid multiple-fiber fibrous insulation was modeled using a thermal model previously used to model heat transfer in flexible single-fiber fibrous insulation. The rigid insulation studied was alumina enhanced thermal barrier (AETB) at densities between 130 and 260 kilograms per cubic meter. The model consists of using the diffusion approximation for radiation heat transfer, a semi-empirical solid conduction model, and a standard gas conduction model. The relevant parameters needed for the heat transfer model were estimated from steady-state thermal measurements in nitrogen gas at various temperatures and environmental pressures. The heat transfer modeling methodology was evaluated by comparison with standard thermal conductivity measurements, and steady-state thermal measurements in helium and carbon dioxide gases. The heat transfer model is applicable over the temperature range of 300 to 1360 K, pressure range of 0.133 to 101.3 x 10(exp 3) Pa, and over the insulation density range of 130 to 260 kilograms per cubic meter in various gaseous environments.

Daryabeigi, Kamran↗

Identifying and Addressing Land Surface Model Deficiencies with Data Assimilation

Land surface models (LSMs) encapsulate our understanding of terrestrial water and energy cycle physics and provide estimates of land surface states and fluxes when and where measurement gaps exist. Gaps in our understanding of the physics are a different issue. Data assimilation can address that issue both directly, through updating of prognostic model variables, or indirectly, when the simulated world conflicts with observation, necessitating adjustment of the model. Here we will focus on the latter case and present several examples, including (1) depth to bedrock adjustment to accommodate assimilated GRACE terrestrial water storage data; (2) steps to prevent immediate melting of assimilated snow cover; (3) irrigation's contribution to evapotranspiration; (4) lessons learned from soil moisture data assimilation; (5) the potential impact of satellite based runoff observation

Rodell, Matthew↗

Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet's mean precipitation.

Global Precipitation Climatology Project (GPCP)↗

Decomposition Technique for Remaining Useful Life Prediction

The prognostic tool disclosed here decomposes the problem of estimating the remaining useful life (RUL) of a component or sub-system into two separate regression problems: the feature-to-damage mapping and the operational conditions-to-damage-rate mapping. These maps are initially generated in off-line mode. One or more regression algorithms are used to generate each of these maps from measurements (and features derived from these), operational conditions, and ground truth information. This decomposition technique allows for the explicit quantification and management of different sources of uncertainty present in the process. Next, the maps are used in an on-line mode where run-time data (sensor measurements and operational conditions) are used in conjunction with the maps generated in off-line mode to estimate both current damage state as well as future damage accumulation. Remaining life is computed by subtracting the instance when the extrapolated damage reaches the failure threshold from the instance when the prediction is made.

Saha, Bhaskar↗

Remote Sensing of Precipitation from Airborne and Spaceborne Radar

Weather radar measurements from airborne or satellite platforms can be an effective remote sensing tool for examining the three-dimensional structures of clouds and precipitation. This chapter describes some fundamental properties of radar measurements and their dependence on the particle size distribution (PSD) and radar frequency. The inverse problem of solving for the vertical profile of PSD from a profile of measured reflectivity is stated as an optimal estimation problem for single- and multi-frequency measurements. Phenomena that can change the measured reflectivity Z(sub m) from its intrinsic value Z(sub e), namely attenuation, non-uniform beam filling, and multiple scattering, are described and mitigation of these effects in the context of the optimal estimation framework is discussed. Finally, some techniques involving the use of passive microwave measurements to further constrain the retrieval of the PSD are presented.

cloud↗