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At least 325 records · Page 18

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Duda, David P.↗

Illinois Disasters: Utilizing NASA Earth Observations to Enhance Drought Monitoring in Illinois

Drought and flooding in Illinois have severe impacts on the communities and ecosystems of the state. Soil moisture is a valuable indicator of drought and flood vulnerability but can be difficult to measure since in situ monitoring is limited to discrete stations throughout the state. The team created a framework to compare in situ, modeled, and NASA satellite soil moisture measurements to increase the spatial coverage of soil moisture monitoring. The team partnered with the Illinois State Weather Survey, USDA Midwest Climate Hub, NOAA Regional Climate Services of the Central Region, NOAA National Integrated Drought Information System’s Midwest Drought Early Warning System, and the NOAA North Central River ForecastCenter. The team standardized and compared soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, modeled soil moisture outputs from NASA’s SPoRT Land Information System (SPoRT-LIS), and in situ measurements from the Illinois State Weather Survey’s Water and Atmospheric Resources Monitoring (WARM) program. Compared to the WARM data, the satellite and modeled data showed seasonally variable differences and bias. The difference was highest in the winter months and lowest in the late summer and early fall months for the SMAP and SPoRT-LIS data products. SPoRT-LIS produced lower seasonal variability and SMAP demonstrated higher correlation values and lower differences. These analyses suggest that both SMAP and SPoRT-LIS products offer unique strengths and limitations when used for soil moisture monitoring

Joshua Green↗

Determination of instrumentation errors from measured data using maximum likelihood method

The maximum likelihood method is used for estimation of unknown initial conditions, constant bias and scale factor errors in measured flight data. The model for the system to be identified consists of the airplane six-degree-of-freedom kinematic equations, and the output equations specifying the measured variables. The estimation problem is formulated in a general way and then, for practical use, simplified by ignoring the effect of process noise. The algorithm developed is first applied to computer generated data having different levels of process noise for the demonstration of the robustness of the method. Then the real flight data are analyzed and the results compared with those obtained by the extended Kalman filter algorithm.

Keskar, D. A.↗

A Systematic Error Correction Method for TOVS Radiances

Treatment of systematic errors is crucial for the successful use of satellite data in a data assimilation system. Systematic errors in TOVS radiance measurements and radiative transfer calculations can be as large or larger than random instrument errors. The usual assumption in data assimilation is that observational errors are unbiased. If biases are not effectively removed prior to assimilation, the impact of satellite data will be lessened and can even be detrimental. Treatment of systematic errors is important for short-term forecast skill as well as the creation of climate data sets. A systematic error correction algorithm has been developed as part of a 1D radiance assimilation. This scheme corrects for spectroscopic errors, errors in the instrument response function, and other biases in the forward radiance calculation for TOVS. Such algorithms are often referred to as tuning of the radiances. The scheme is able to account for the complex, air-mass dependent biases that are seen in the differences between TOVS radiance observations and forward model calculations. We will show results of systematic error correction applied to the NOAA 15 Advanced TOVS as well as its predecessors. We will also discuss the ramifications of inter-instrument bias with a focus on stratospheric measurements.

Joiner, Joanna↗

Two biased estimation techniques in linear regression: Application to aircraft

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Klein, Vladislav↗

The X-Ray Spectrum of WZ Sagittae

We carried out an Advanced Satellite for Cosmology and Astrophysics (ASCA) observation of WZ Sagittae, to obtain the first X-ray spec- trum and to search for an X-ray counterpart near the well-known optical signal of 27.87 s. At around the same epoch, we carried out a similar search in ultraviolet radiation with the Faint Object Spectrograph (FOS) aboard the Hubble Space Telescope (HST). These experiments were done to test the hypothesis that the signal arises from rapid white dwarf rotation. The result generally confirmed that hypothesis, because signals were apparently detected at 27.87 s in both UV and hard X-ray light. But the detailed results were somewhat confusing, not exactly as simple as we dreamed in the proposal. The X-ray signal only emerges with fairly subtle methods of data analysis: either a "period-biased" search, or a sorting of X-ray photons into hard/soft - thus the detections are slightly marred by the taint of a posterz'ori reasoning. The UV data suffer a different but also worrisome problem: although 27.87 s is definitely detected, it's weaker than two other signals, at 28.22 and 29.69 s. That's quite surprising - we expected that the UV power spectrum would be simple, on the grounds that the UV flux distribution is nearly a pure white dwarf. Considered in isolation, such behavior from a white dwarf should be considered evidence for the pulsation hypothesis. The X-ray spectrum was interesting, mostly by virtue of what it did not show. It was essentially a pure thermal bremsstrahlung with kT = 5 keV, with only a very weak Fe K complex. This probably signifies origin near the central white dwarf and heating from accretion (propellor heating farther out would give lower densities and more cooling by emission lines). We published a paper reporting most of these details (Patterson et al. (1998), PASP, 110, 403), Much of the world accepts now that WZ Sge contains a rapidly spinning white dwarf - the fastest spin of any accreting white dwarf.

Patterson, Joseph↗

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

Surface-state spectra from thick-oxide MOS tunnel junctions

The conductance and capacitance of thick-oxide MOS tunnel junctions (SiO2 thickness 40 to 65 A) have been measured from 35 Hz to 210 kHz. It is demonstrated that the use of a thick-oxide MOS tunnel junction makes it possible to obtain the surface-state data throughout the whole silicon band gap with better resolution and better sensitivity than the conventional MOS capacitance techniques. A slight departure from equilibrium may occur in the voltage range where large tunnel current flows. Corrections to the energy scale must be made in this voltage range. A method for the evaluation of the junction quality is discussed. The simplified equivalent circuits necessary for the calculation of surface-state data are constructed under various bias conditions by an approach different from that used in a previously published work. The present work supports the model that at least some of the observed surface states are a consequence of the diffusion of contact metals into the oxide.

Ma, T. P.↗

Recent advances in multispectral sensing of ocean surface temperature from space

Visual and infrared measurements from the five channel AVHRR on the NOAA-7 satellite are used operationally to derive sea surface temperatures. The multichannel data perform daytime and nighttime cloud detection tests, and the several atmospheric window channels in the thermal infrared correct for atmospheric attenuation. Monitoring of the sea surface temperature product with buoy data indicates stability in mean bias and rms difference with little variation by season or geographic area. Global mapping enables the derivation of monthly mean isotherms, monthly and annual changes, and anomaly patterns relative to climatology. Problems are associated with noise in the 3.7 micro m window channel, and with the injection of substantial volcanic aerosol into the stratosphere by the El Chichon eruption. Multichannel sea surface temperature charts are used to study phenomena such as equatorial long waves and the recent El Nino episode.

Mcclain, E. P.↗

Assessing photovoltaic module degradation and lifetime from long term environmental tests

The photovoltaic module failure mechanisms related to temperature, humidity, and electrical bias are analyzed using the data collected over a period of 20 years from various sites in the U.S. The approach is based on measuring the rate dependence of the mechanisms on site stress levels, and then using the rate data to analytically estimate the field life by means of computer models of the site environment. A correlation is established between the accelerated constant-stress testing and the time-varying field exposures. Test results are presented for two failure mechanisms for a module design featuring polyvinyl butyral encapsulant for the temperature range of 85 to 100 C and 85-percent relative humidity.

Otth, D. H.↗

Retrieval of sea surface temperatures from HIRS2/MSU

The methods used at the Goddard Laboratory for Atmospheres (GLA) to retrieve sea surface temperatures from HIRS2/MSU data for the last 2 months of the NASA sea surface temperature intercomparison workshop are described. Results are shown that compare anomaly fields produced by using data from ships, AVHRR, and HIRS2/MSU for these months. Monthly mean fields derived from AVHRR and HIRS2 data show roughly comparable statistical accuracy compared to ship fields. Errors in the HIRS2 fields appear more random, while AVHRR data have larger regionally dependent biases and show large area spatially coherent errors. The random errors in the HIRS2 fields should be further reduced by performing the retrievals at a higher spatial resolution.

Susskind, J.↗

Sensitivity of surface radiative fluxes to meteorological parameter errors

A parameterized radiative transfer model is employed to estimate longwave fluxes, while shortwave fluxes are estimated with a broadband absorption and scattering technique. Meteorological parameters of surface radiative fluxes are the profiles of temperature and cloud cover, ozone, water vapor and aerosols. A sensitivity study is presented to estimate the magnitudes of biases in the computed fluxes resulting from the biases in the satellite meteorological data.

Ritchey, Nancy A.↗

Raman Lidar Measurements of Water Vapor and Cirrus Clouds During The Passage of Hurricane Bonnie

The NASA/GSFC Scanning Raman Lidar (SRL) was stationed on Andros Island in the Bahamas during August - September, 1998 as a part of the third Convection and Moisture Experiment (CAMEX-3) which focussed on hurricane development and tracking. During the period August 21 - 24, hurricane Bonnie passed near Andros Island and influenced the water vapor and cirrus cloud measurements acquired by the SRL. Two drying signatures related to the hurricane were recorded by the SRL and other sensors. Cirrus cloud optical depths (at 351 nm) were also measured during this period. Optical depth values ranged from less than 0.01 to 1.5. The influence of multiple scattering on these optical depth measurements was studied. A correction technique is presented which minimizes the influences of multiple scattering and derives information about cirrus cloud optical and physical properties. The UV/IR cirrus cloud optical depth ratio was estimated based on a comparison of lidar and GOES measurements. Simple radiative transfer model calculations compared with GOES satellite brightness temperatures indicate that satellite radiances are significantly affected by the presence of cirrus clouds if IR optical depths are approximately 0.005 or greater. Using the ISCCP detection threshold for cirrus clouds on the GOES data presented here, a high bias of up to 40% in the GOES precipitable water retrieval was found.

Whiteman, D. N.↗

Status of TRMM Monthly Estimates of Tropical Precipitation

Nearly three years of Tropical Rainfall Measuring Mission Satellite (TRMM Satellite) monthly estimates of tropical surface rainfall are analyzed to document and understand the differences among the TRMM-based estimates and how these differences relate to the pre-TRMM estimates and current operational analyses. Variation among the TRMM estimates is shown to be considerably smaller than among a pre-TRMM collection of passive microwave-based products. Use of both passive and active microwave techniques in TRMM should lead to increased confidence in converged estimates. Current TRMM estimates are shown to have a range of about 20% for the tropical ocean as a whole, with variations in heavily raining ocean areas of the ITCZ and SPCZ having differences over 30%. In mid-latitude ocean areas the differences are smaller. Over land there is a distinct difference between the tropics and mid-latitude with a reversal between some of the products as to which tends to be relatively high or low. Comparisons of TRMM estimates with ocean atoll and land gauge information point to products that might have significant regional biases. The radar-based product is significantly low biased compared with atoll raingauge data, while the passive microwave product is significantly high compared to raingauge data in the deep tropics. The evolution of rainfall patterns during the recent change from intense El Nino to a long period of La Nina and then a gradual return to near neutral conditions is described using TRMM. The time history of integrated rainfall over the tropical oceans (and land) during this period differs among the passive and active microwave TRMM estimates.

Adler, Robert F.↗

Definition of International GPM GV Research Program

The Global Precipitation Measurement (GPM) Mission will consist of a constellation of rain-measuring satellites, the main member of which (the core satellite) will serve as the measurement reference to the other members of the constellation. The core satellite is being developed jointly by the National Aeronautics and Space Administration (NASA) and the newly-named Japan Aerospace Exploration Agency (JAXA -- previously NASDA) along with its government partner, the Communications Research Laboratory (CRL). The GPM mission was proposed as a follow-up mission to the Tropical Rainfall Measuring Mission (TRMM) by both NASA and NASDA based on the unparalleled scientific success of TRMM, and has recently been joined by the European Space Agency (ESA) via its formulation of the European GPM mission (i.e., EGPM). GPM is an ambitious mission designed to produce accurate and frequent global observations of precipitation (both rain and snow) made possible by replacing the TRMM satellite with the new core satellite carrying an advanced radar-radiometer system, and serving as the centerpiece for the constellation of some eight (8) additional satellites being provided through international cooperation. The core satellite is to be flown up to high latitudes (inclined some 65-70 degrees), and will carry a Ku/Ka-band, nadir-scanning, dual-frequency precipitation radar (DPR) that is being developed by JAXA and CRL, along with a large aperture, extended frequency-range, conically-scanning passive microwave radiometer being developed by NASA and its industrial partners. Each constellation satellite will also carry some type of multi-channel passive microwave radiometer (as well as a multi-beam Ka-band radar in the case of EGPM) whose rain estimates will be calibrated and referenced to those made by the core satellite, producing for the first time fully-global, continuous, and bias-free precipitation datasets. GPM data will be delivered in near-realtime, taking a major step toward the operational use of precipitation information for model initialization and data assimilation in a number of application areas such as hazardous weather forecasting, flood warning, fresh water resource assessment, and crop growth prediction. In addition, GPM data will complement the now-existing global temperature record, allowing for improved assessments of climate change, particularly those processes in which the global water cycle both forces and responds to climatic drifts in global temperature conditions. A foremost element of this international constellation mission is a parallel international ground validation (GV) network. This GV network is needed to determine uncertainties in the rain retrievals, critical for application of the retrieval information in weather and hydrometeorological modeling and climate diagnostics, as well as assurances that the satellite retrievals of surface rainfall are consistent with those actually measured at the surface. The key aspects of this network is that it must be worldwide and created through the GPM partnership process. Therefore the network will consist of a confederation of government agencies, academic organizations, private institutions, and individual scientists from a collection of nations who have initiated the process by gathering in Abingdon to develop the fundamentals of the international GPM GV research programme. Therefore in keeping with our responsibilities as the front-runners of the programme, the main objectives of this workshop are: (1) to present and share opinions on interests, perspectives, and concerns about GPM GV research; (2) to examine the conceptual and/or planned GPM GV site templates from NASA, NASDA, ESA, and other partners; (3) to define the main scientific objectives of the international GPM GV research programme; (4) to formulate a preliminary set of international GPM GV science and measurement requirements; and (5) to convene a Steering Committee to aid the organization of the GPM GV program, to document its science implementation plans, and to aid planning for follow-up GPM GV meetings.

Smith, Eric A.↗

Research on TRMM and GPM Through Collaboration Between JAXA & NASA

The Japan Aerospace Exploration Agency (JAXA) is conducting joint research with the Communications Research Laboratory (CRL) and the National Aeronautics and Space Administration (NASA) on a new constellation satellite observation project called Global Precipitation Measurement (GPM), the main satellite of which is planned for launch in 2008 by JAXA. This GPM project was proposed as a follow-up mission to the Tropical Rainfall Measuring Mission (TRMM) by both the Japanese and American sides based on the unparalleled scientific success of TRMM. A major reason for TRMM's success was the use of the worlds first spaceborne rain radar, the Precipitation Radar (PR) system developed by the National Space Development Agency of Japan (NASDA, now JAXA) and CRL. Measurements from this instrument have ushered in many new scientific findings and have opened a new era of precipitation measuring from space. GPM is an ambitious project which will produce accurate and frequent global observations of precipitation (both rain and snow) made possible by replacing TRMM with a new core satellite carrying an advanced radar-radiometer system, and serving as the centerpiece for a constellation of some eight (8) additional satellites being provided through international cooperation. The core satellite is to be flown up to high latitudes (inclined some 65-70 degrees), and will carry a dual-frequency precipitation radar (DPR) that will be newly developed by JAXA and CRL, along with a large aperture, extended frequency-range passive microwave radiometer being provided by NASA. Each constellation satellite will also carry some type of multi-channel passive microwave radiometer whose rain estimates will be calibrated and referenced to those made by the core satellite, producing for the first time fully-global, continuous, and bias-free precipitation datasets. GPM data will be delivered in near-realtime, taking a major step toward the operational use of precipitation information for model initialization and data assimilation in a number of application areas such as hazardous weather forecasting, flood warning, fresh water resource assessment, and crop growth prediction. In addition, GPM data will complement the now-existing global temperature record, allowing for improved assessments of climate change, particularly those processes in which the global water cycle both forces and responds to climatic drifts in global temperature conditions.

Smith, Eric A.↗

The Psychology of Cost Estimating

Cost estimation for large (and even not so large) government programs is a challenge. The number and magnitude of cost overruns associated with large Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) programs highlight the difficulties in developing and promulgating accurate cost estimates. These overruns can be the result of inadequate technology readiness or requirements definition, the whims of politicians or government bureaucrats, or even as failures of the cost estimating profession itself. However, there may be another reason for cost overruns that is right in front of us, but only recently have we begun to grasp it: the fact that cost estimators and their customers are human. The last 70+ years of research into human psychology and behavioral economics have yielded amazing findings into how we humans process and use information to make judgments and decisions. What these scientists have uncovered is surprising: humans are often irrational and illogical beings, making decisions based on factors such as emotion and perception, rather than facts and data. These built-in biases to our thinking directly affect how we develop our cost estimates and how those cost estimates are used. We cost estimators can use this knowledge of biases to improve our cost estimates and also to improve how we communicate and work with our customers. By understanding how our customers think, and more importantly, why they think the way they do, we can have more productive relationships and greater influence. By using psychology to our advantage, we can more effectively help the decision maker and our organizations make fact-based decisions.

Price, Andy↗

Flowing Plasma Interaction with an Electric Sail Tether Element

Electric sails are a relatively new concept for providing high speed propellant-less propulsion. Employing multiple tethers biased to high positive voltage levels (kV), electric sails are designed to gain momentum from the solar wind by repelling solar wind protons. To maximize the area of the sail that interacts with the solar wind, electric sails rely on the formation of a large plasma sheath around each small diameter tether. Motivated by interest in advancing the development of electric sails, a set of laboratory tests has been conducted to study the interaction of a drifting plasma with a sheath formed around a small diameter tether element biased at positive voltages. The laboratory test setup was created with Debye length scaling in mind to offer a path to extrapolate (via modeling) to full scale electric sail missions. Using an instrument known as a Differential Ion Flux Probe (DIFP) the interaction between a positively biased tether element and a drifting plasma has been measured for several scenarios. Clear evidence of the tether element sheath deflecting ions has been obtained. Maps of the flow angle downstream from the tether element have been made and they show the influence of the plasma sheath. Finally, electron current collection measurements have been made for a wide range of plasma conditions and tether element bias voltages. The electron collection data will have an impact on electric sail power requirements, as high voltage power supplies and electron guns will have to be sized to accommodate the electron currents collected by each tether.

Schneider, Todd↗