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At least 181 records · Page 10

Use of near infrared correlation spectroscopy for quantitation of surface iron, absorbed water and stored electronic energy in a suite of Mars soil analog materials

A number of questions concerning the surface mineralogy and the history of water on Mars remain unresolved using the Viking analyses and Earth-based telescopic data. Identification and quantitation of iron-bearing clays on Mars would elucidate these outstanding issues. Near infrared correlation analysis, a method typically applied to qualitative and quantitative analysis of individual constituents of multicomponent mixtures, is adapted here to selection of distinctive features of a small, highly homologous series of Fe/Ca-exchanged montmorillonites and several kalinites. Independently determined measures of surface iron, relative humidity and stored electronic energy were used as constituent data for linear regression of the constituent vs. reflectance data throughout the spectral region 0.68 to 2.5 micrometers. High correlations were found in appropriate regions for all three constituents, though that with stored energy is still considered tenuous. Quantitation was improved using 1st and 2nd derivative spectra. High resolution data over a broad spectral range would be required to quantitatively identify iron-bearing clays by remotely sensed reflectance.

Coyne, Lelia M.↗

Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture data for each profile location and pressure level. Analyses are run to produce quasi-real-time regional weather forecasts over the continental U.S. The preliminary assessment of the impact of the AIRS profiles will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes.

Zavodsky, Brad↗

Atmospheric infrared sounder on AIRS with emphasis on level 2 products

The Atmospheric Infrared Sounder (AIRS) was launched aboard EOS Aqua in May of 2002. AIRS is a grating spectrometer with almost 2400 channels covering the 3.74 to 15.40 micron spectral region with a nominal spectral resolution ((nu)/(delta)(nu)) of 1200, with some gaps. In addition, AIRS has 4 channels in the NIR/VIS region. The AIRS operates in conjunction with the microwave sounders Advanced Microwave Sounding Unit (AMSU-A) and Humidity Sounder of Brazil (HSB). The microwave sounders are mainly used for cloud clearing of IR radiances, or to remove the effect of cloud on the IR radiances.

infrared spectrometers↗

Raman Lidar Measurements of Aerosol Extinction and Backscattering: Derivation of Aerosol Real Refractive Index, Single-Scattering Albedo, and Humidification Factor using Raman Lidar and Aircraft Size Distribution - Report 2

Aerosol backscattering and extinction profiles measured by the NASA Goddard Space Flight Center Scanning Raman Lidar (SRL) during the remote cloud sensing (RCS) intensive operations period (IOP) at the Department of Energy Atmospheric Radiation Measurement (ARM) southern Great Plains (SGP) site during two nights in April 1994 are discussed. These profiles are shown to be consistent with the simultaneous aerosol size distribution measurements made by a PCASP (Passive Cavity Aerosol Spectrometer Probe) optical particle counter flown on the University of North Dakota Citation aircraft. We describe a technique which uses both lidar and PCASP measurements to derive the dependence of particle size on relative humidity, the aerosol real refractive index n, and estimate the effective single-scattering albedo Omega(sub 0). Values of n ranged between 1.4-1.5 (dry) and 1.37-1.47 (wet); Omega(sub 0) varied between 0.7 and 1.0. The single-scattering albedo derived from this technique is sensitive to the manner in which absorbing particles are represented in the aerosol mixture; representing the absorbing particles as an internal mixture rather than the external mixture assumed here results in generally higher values of Omega(sub 0). The lidar measurements indicate that the change in particle size with relative humidity as measured by the PCASP can be represented in the form discussed by Hattel with the exponent gamma = 0.3 + or - 0.05. The variations in aerosol optical and physical characteristics captured in the lidar and aircraft size distribution measurements are discussed in the context of the meteorological conditions observed during the experiment.

Ferrare, R. A.↗

Noninvasive Breath Analysis Using NASA E-Nose Technology for Health Assessment

Clinical breath analysis is based on the fact that many important metabolites and biomarker molecules are present at detectable levels in exhaled breath, and many of these molecules correlate with human disease or correlate with physiological states that could lead to a decline in health. Presented is a technology that utilizes an array of chemical sensors combined with humidity, temperature and pressure for real time breath analysis to correlate the chemical information in the breath with the state and functioning of different human organs. For example, a marker for pulmonary inflammation processes of the lower respiratory tract, e.g. asthma, is the increase of the nitrogen oxide (NO) concentration in breath. Other volatile biomarkers may correlate with infectious process, metabolic conditions and inflammatory diseases, such as traumatic brain injury (TBI). This technology is also called "electronic nose" (E-Nose) in the sense that the device can mimic human nose to smell odors using a pattern recognition technique to analyze the sensor array data. Breath sampling is non-invasive and can be analyzed in real-time.

Li, Jing↗

GPM Mission Overview and U.S. Science Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products [1-2]. Water is fundamental to life on Earth. Knowing where and how much rain and snow falls globally is vital to understanding how weather and climate impact both our environment and Earth's water and energy cycles, including effects on agriculture, fresh water availability, and responses to natural disasters. Since rainfall and snowfall vary greatly from place to place and over time, satellites can provide more uniform observations of rain and snow around the globe than ground instruments, especially in areas where surface measurements are difficult. Relative to current global rainfall products, GPM data products will be characterized by: (l) more accurate instantaneous precipitation measurements (especially for light rain and cold-season solid precipitation), (2) more frequent sampling by an expanded constellation of domestic and international microwave radiometers including operational humidity sounders, (3) intercalibrated microwave brightness temperatures from constellation radiometers within a unified framework, and (4) physical-based precipitation retrievals from constellation radiometers using a common a priori cloud/hydrometeor database derived from GPM Core sensor measurements. The cornerstone of the GPM mission is the deployment of a Core Observatory in a unique 65 non-Sun-synchronous orbit to serve as a physics observatory and a reference standard to unify precipitation measurements by a constellation of dedicated and operational passive microwave sensors. The design of the GPM Core Observatory is an advancement of the Tropical Rainfall Measuring Mission (TRMM)'s highly successful rain-sensing package. The Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a multichannel (l0-183 GHz) GPM Microwave Radiometer (GMI). Since light rain and falling snow account for a significant fraction of precipitation occurrence in middle and high latitudes, the GPM instruments extend the capabilities of the TRMM sensors to detect falling snow, measure light rain, and provide, for the first time, quantitative estimates of microphysical properties of precipitation particles. The combined use of DPR and GMI measurements will place greater constraints on possible solutions to radiometer retrievals to improve the accuracy and consistency of precipitation retrievals from all constellation radiometers. The GMI uses 13 different microwave channels to observe energy from the different types of precipitation through clouds for estimating everything from heavy to light rain and for detecting falling snow. As the satellite passes over Earth, the GMI constantly scans a region 885 kilometers across. The Ball Aerospace and Technology Corporation built the GMI under contract with NASA Goddard Space Flight Center. The DPR provides three-dimensional information about precipitation particles derived from reflected energy by these particles at different heights within the cloud system. The two frequencies of the DPR also allow the radar to infer the sizes of precipitation particles and offer insights into a storm's physical characteristics. The Ka-band frequen~y scans across a region of 125 kilometers and is nested within the wider scan of the Ku-band frequency of 245 kilometers. The Japan Aerospace and Exploration Agency (JAXA) and Japan's National Institute of Information and Communications Technology (NICT) built the DPR. The Core Observatory satellite will fly at an altitude of 253 miles (407 kilometers) in a non-Sun-synchronous orbit that covers the Earth from 65 S to 65 N - from about the Antarctic Circle to the Arctic Circle. The GPM Core Observatory is being developed and tested at NASA Goddard Space Flight Center. Once complete, a Japanese H-lIA rocket will carry thPM Core Observatory into orbit from Tanegashima Island, Japan in 2014. The GPM constellation is envisioned to comprise 8 or more microwave sensors provided by partners, including both conical imagers and cross-track sounders. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Additional partnerships are under development to include microwave radiometers on the French-Indian Megha-Tropiques satellite and U.S. Defense Meteorological Satellite Program (DMSP) satellites, as well as humidity sounders or precipitation sensors on operational satellites such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), NOAA-NASA Joint Polar Satellite System (JPSS) satellites, European MetOp satellites, and DMSP follow-on sensors. In addition, data from Chinese and Russian microwave radiometers may be available through international cooperation under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). GPM's next-generation global precipitation data will lead to scientific advances and societal benefits in the following areas: (1) Improved knowledge of the Earth's water cycle and its link to climate change (2) New insights into precipitation microphysics, storm structures and large-scale atmospheric processes (3) Better understanding of climate sensitivity and feedback processes (4) Extended capabilities in monitoring and predicting hurricanes and other extreme weather events (5) Improved forecasting capabilities for natural hazards, including floods, droughts and landslides. (6) Enhanced numerical prediction skills for weather and climate (7) Better agricultural crop forecasting and monitoring of freshwater resources. An overview of the GPM mission concept and science activities in the United States, together with an update on international collaborations in radiometer intercalibration and ground validation, will be presented.

Hou, Arthur Y.↗

Session on modeling of radiative transfer processes

The session on modeling of radiative transfer processes is reviewed. Six critical issues surfaced in the discussion concerning scale-interactive radiative processes relevent to the mesoscale convective systems (MCS's). These issues are the need to expand basic knowledge of how MCS's influence climate through extensive cloud shields and increased humidity in the upper troposphere; to improve radiation parameterizations used in mesoscale and General Circulation Model (GCM) models; to improve our basic understanding of the influence of radiation on MCS dynamics due to diabatic heating, production of condensate, and vertical and horizontal heat fluxes; to quantify our understanding of radiative impacts of MCS's on the surface and free atmosphere energy budgets; to quantify and identify radiative and microphysical processes important in the evolution of MCS's; and to improve the capability to remotely sense MCS radiative properties from space and ground-based systems.

Flatau, Piotr↗

Optical Breath Gas Sensor for Extravehicular Activity Application

The function of the infrared gas transducer used during extravehicular activity (EVA) in the current space suit is to measure and report the concentration of carbon dioxide (CO2) in the ventilation loop. The next generation Portable Life Support System (PLSS) requires next generation CO2 sensing technology with performance beyond that presently in use on the Shuttle/International Space Station extravehicular mobility unit (EMU). Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. A laser diode (LD) spectrometer based on wavelength modulation spectroscopy (WMS) is being developed for this purpose by Vista Photonics, Inc. Two prototype devices were delivered to NASA Johnson Space Center (JSC) in September 2011. The sensors incorporate a laser diode based CO2 channel that also includes an incidental water vapor (humidity) measurement and a separate oxygen (O2) channel using a vertical cavity surface emitting laser (VCSEL). Both prototypes are controlled digitally with a field-programmable gate array (FPGA)/microcontroller architecture. Based on the results of the initial instrument development, further prototype development and testing of instruments leveraging the lessons learned were desired. The present development extends and upgrades the earlier hardware to the Advanced PLSS 2.0 test article being constructed and tested at JSC. Various improvements to the electronics and gas sampling are being advanced by this project. The combination of low power electronics with the performance of a long wavelength laser spectrometer enables multi-gas sensors with significantly increased performance over that presently offered in the EMU. .

Wood, William R.↗

Optical Breath Gas Sensor for Extravehicular Activity Application

The function of the infrared gas transducer used during extravehicular activity in the current space suit is to measure and report the concentration of carbon dioxide (CO2) in the ventilation loop. The next generation portable life support system (PLSS) requires next generation CO2 sensing technology with performance beyond that presently in use on the Space Shuttle/International Space Station extravehicular mobility unit (EMU). Accommodation within space suits demands that optical sensors meet stringent size, weight, and power requirements. A laser diode spectrometer based on wavelength modulation spectroscopy is being developed for this purpose by Vista Photonics, Inc. Two prototype devices were delivered to NASA Johnson Space Center (JSC) in September 2011. The sensors incorporate a laser diode-based CO2 channel that also includes an incidental water vapor (humidity) measurement and a separate oxygen channel using a vertical cavity surface emitting laser. Both prototypes are controlled digitally with a field-programmable gate array/microcontroller architecture. The present development extends and upgrades the earlier hardware to the Advanced PLSS 2.0 test article being constructed and tested at JSC. Various improvements to the electronics and gas sampling are being advanced by this project. The combination of low power electronics with the performance of a long wavelength laser spectrometer enables multi-gas sensors with significantly increased performance over that presently offered in the EMU.

Wood, William R.↗

Seasonal Monitoring and Estimation of Regional Aerosol Distribution over Po Valley, Northern Italy, Using a High-Resolution MAIAC Product

In this work, the new 1-km-resolved Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is employed to characterize seasonal AOD-PM10 correlations over northern Italy. The accuracy of the new dataset is assessed versus the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data, retrieved at 0.55 microns with spatial resolution of 10 km (MYD04). We focused on evaluating the ability of these two products to characterize both temporal and spatial distributions of aerosols within urban and suburban areas. Ground PM10 measurements were obtained from 73 of the Italian Regional Agency for Environmental Protection (ARPA) monitoring stations, spread across northern Italy, for a three-year period from 2010 to 2012. The Po Valley area (northern Italy) was chosen as the study domain because of severe urban air pollution, resulting from the highest population and industrial manufacturing density in the country, being located in a valley where two surrounding mountain chains favor the stagnation of pollutants. We found that the global correlations between PM10 and AOD are R(sup 2) = 0.83 and R(sup 2) = 0.44 for MYD04_L2 and for MAIAC, respectively, suggesting for a greater sensitiveness of the high-resolution product to small-scale deviations. However, the introduction of Relative Humidity (RH) and Planetary Boundary Layer (PBL) depth corrections gave a significant improvement to the PM AOD correlation, which led to similar performance: R(sup 2) = 0.96 for MODIS and R(sup 2) = 0.95 for MAIAC. Furthermore, the introduction of the PBL information in the corrected AOD values was found to be crucial in order to capture the clear seasonal cycle shown by measured PM10 values. The study allowed us to define four seasonal linear correlations that estimate PM10 concentrations satisfactorily from the remotely sensed MAIAC AOD retrieval. Overall, the results show that the high resolution provided by MAIAC retrieval data is much more relevant than 10km MODIS data to characterize PM10 in this region of Italy which has a pretty limited geographical domain, but a broad variety of land usages and consequent particulate concentrations.

MODIS↗

New Perspectives on Blowing Snow Transport, Sublimation, and Layer Thermodynamic Structure over Antarctica

Blowing snow over Antarctica is a widespread and frequent event. Satellite remote sensing using lidar has shown that blowing snow occurs over 70% of the time over large areas of Antarctica in winter. The transport and sublimation of blowing snow are important terms in the ice sheet mass balance equation and the latter is also an important part of the hydrological cycle. Until now the only way to estimate the magnitude of these processes was through model parameterization. We present a technique that uses direct satellite observations of blowing snow and model (MERRA-2) temperature and humidity fields to compute both transport and sublimation of blowing snow over Antarctica for the period 2006 to 2016. The results show a larger annual continent-wide integrated sublimation than current published estimates and a significant transport of snow from continent to ocean. The talk will also include the lidar backscatter structure of blowing snow layers that often reach heights of 200 to 300 m as well as the first dropsonde measurements of temperature, moisture and wind through blowing snow layers.

Palm, Steve↗

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

Climate Forcing Data↗

Using passive, thermal remote sensing techniques for detecting subsurface gravel accumulations in vegetated, unconsolidated sedimentary terrains

Multiband radiometric data from an airborne imaging thermal scanner are being studied for use in finding buried gravel deposits. The techniques are based on measuring relative differences in the thermal properties between gravel-laden targets and the surrounding gravelless background. These properties are determined from modeling the spectral radiant emittance recorded over both types of surfaces in conjunction with ground measurements of the most significant heat flows above and below the surface. Thermodynamic properties of sampled materials from control sites are determined, and diurnal and annual subsurface heat waves are recorded. Thermal models that account for heat exchange at the surface, as well as varying levels of soil moisture, humidity, and vegetation, are needed for adaptation and modification to simulate the physical and radiative environments of this region.

Burns, Gregory S.↗

Verification of Atmospheric Signals Associated with Major Seismicity by Space and Terrestrial Observations

Observations from the last twenty years suggest the existence of electromagnetic (EM) phenomena during or preceding some earthquakes [Haykawa et a!, 2004; Pulinets at al, 1999,2004, 2006, Ouzounov et all 2007 and Liu et all 20041. Both our previous studies [Pulinets at al, 2005, 2006, Ouzounov et al, 2006, 20071 and the latest review by the Earthquake Remote Precursor Sensing panel [ERPS; 2003- 20051; have shown that there were precursory atmospheric TIR signals observed on the ground and in space associated with several recent earthquakes. [Tramutoli at al, 2005, 2006, Cervone et al, 2006, Ouzounov et all 2004,2006JT.o study these signals, we applied both multi parameter statistical analysis and data mining methods that require systematic measurements from an Integrated Sensor Web of observations of several physical and environmental parameters. These include long wave earth infra-red radiation, ionospheric electrical and magnetic parameters, temperature and humidity of the boundary layer, seismicity and may be associated with major earthquakes. Our goal is to verify the earthquake atmospheric correlation in two cases: (i) backward analysis - 2000-2008 hindcast monitoring of multi atmospheric parameters over the Kamchatka region, Russia ; and (ii) forward real-time alert analysis over different seismo-tectonic regions for California, Turkey, Taiwan and Japan. Our latest results, from several post-earthquake independent analyses of more then 100 major earthquakes, show that joint satellite and some ground measurements, using an integrated web, could provide a capability for observing pre-earthquake atmospheric signals by combining the information from multiple sensors into a common framework. Using our methodology, we evaluated and compared the observed signals preceding the latest M7.9 Sichuan earthquake (0511212008), M8.0 earthquake in Peru (0811512007), M7.6 Kashmir earthquake (1010812005) and M9.0 Sumatra earthquake (1212812004). We found evidence of the systematic appearance of both atmospheric and ionospheric anomalies preceding most of the major events during the period of our analysis 2001 -2008.

Taylor, Patrick↗

Feasibility Assessment of an EVA Glove Sensing Platform to Evaluate Potential Hand Injury Risk Factors

Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). When the gloves are pressurized, they restrict movement and create pressure points during tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally more severe injuries such as onycholysis. A brief review of the Lifetime Surveillance of Astronaut Health's injury database reveals that 58% of total astronaut hand and arm injuries from NBL training between 1993 and 2010 occurred either to the fingernail, MCP, or fingertip. The purpose of this study was to assess the potential of using small sensors to measure force acting on the fingers and hand within pressurized gloves and other variables such as blood perfusion, skin temperature, humidity, fingernail strain, skin moisture, among others. Tasks were performed gloved and ungloved in a pressurizable glove box. The test demonstrated that fingernails saw greater transverse strain levels for tension or compression than for longitudinal strain, even during axial fingertip loading. Blood perfusion peaked and dropped as the finger deformed during finger presses, indicating an initial dispersion and decrease of blood perfusion levels. Force sensitive resistors to force plate comparisons showed similar force curve patterns as fingers were depressed, indicating suitable functionality for future testing. Strategies for proper placement and protection of these sensors for ideal data collection and longevity through the test session were developed and will be implemented going forward for future testing.

Reid, Christopher R.↗

A multi-sensor analysis of Nimbus 5 data on 22 January 1973

The Nimbus 5 meteorological satellite carried aloft a full complement of radiation sensors, the data from which were analyzed and intercompared during orbits 569-570 on 22 January 1973. The electrically scanning microwave radiometer (ESMR) which sensed passive microwave radiation in the 19.35 GHz region, delineated rain areas over the ocean off the U.S. east coast, in good agreement with WSR-57 and FPS-77 radar imagery and permitted the estimation of rainfall rates in this region. Residual ground water in the lower Mississippi Valley, which resulted from abnormal rainfall in previous months, was indicated under clear sky conditions by soil brightness temperature values in the Nimbus 5 ESMR and U.S. Air Force Data Acquisition and Processing Program (DAPP) IR data. The temperature-humidity infrared radiometer showed the height and spatial configuration of frontal clouds along the east coast and outlined the confluence of a polar jet stream with a broad sub-tropical jet stream along the U.S. Gulf Coast. Temperature profiles from three vertical temperature sounders, the infrared temperature profile radiometer (ITPR), the Nimbus E microwave spectrometer (NEMS) and the selective chopper radiometer (SCR) were found to be in good agreement with related radiosonde ascents along orbit 569 from the sub-tropics to the Arctic Circle.

Allison, L. J.↗

Remote Strain Sensing of CFRP Using Microwave Frequency Domain Reflectometry

NASA's Advanced Composites Project is investigating technologies that increase automated remote inspection of aircraft composite structures. Therefore, microwave Frequency Domain Reflectometry (FDR) is being investigated as a method of enabling rapid remote measurement of strain occurring at the first ply of a composite fiber reinforced polymer (CFRP) structure using Radio Frequency (RF) Electro-Magnetic (EM) radiation. While microwave reflectometry has been used to detect disbonds in CFRP structures, its use in detecting strain has been limited. This work will present data demonstrating the measurement of the reactance changes due to loading conditions that are indicative of strain in a CFRP structure. In addition, the basic EM signature will be presented along with an analysis of temperature and humidity effects.

Wilson, William C.↗

Statistical Quality Control of Moisture Data in GEOS DAS

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

Dee, D. P.↗