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Design of polymeric electrolytic hygrometer improved to meet need for reliable measurements of relative humidity in harsh environments of pulpmills and papermills. Redesigned sensor head features shorter, more-rigidly-held sensing element, less vulnerable than previous version to swell and loss of electrical contact. Useful for control of batch dryers in food and pharmaceutical industries.
The International Space Station (ISS) will soon have a platform for conducting fundamental research of Large Plants. Plant Habitat (PH) is designed to be a fully controllable environment for high-quality plant physiological research. PH will control light quality, level, and timing, temperature, CO2, relative humidity, and irrigation, while scrubbing ethylene. Additional capabilities include leaf temperature and root zone moisture and oxygen sensing. The light cap will have red (630 nm), blue (450 nm), green (525 nm), far red (730 nm) and broad spectrum white LEDs. There will be several internal cameras (visible and IR) to monitor and record plant growth and operations.
The NASA Giovanni data analysis system has been recognized as a useful tool to access and analyze many different types of remote sensing data. The variety of environmental data types has allowed the use of Giovanni for different application areas, such as agriculture, hydrology, and air quality research. The use of Giovanni for researching connections between public health issues and Earths environment and climate, potentially exacerbated by anthropogenic influence, has been increasingly demonstrated. In this communication, the pertinence of several different data parameters to public health will be described. This communication also provides a case study of the use of remote sensing data from Giovanni in assessing the associations between seasonal influenza and meteorological parameters. In this study, logistic regression was employed with precipitation, temperature and specific humidity as predictors. Specific humidity was found to be associated (p 0.05) with influenza activity in both temperate and tropical climate. In the two temperate locations studied, specific humidity was negatively correlated with influenza; conversely, in the three tropical locations, specific humidity was positively correlated with influenza. Influenza prediction using the regression models showed good agreement with the observed data (correlation coefficient of 0.50.83).
It is known that capacitance-sensing, rotor-blade-tip-clearance measurement systems suffer from a strong dependency on probe tip temperature and humidity. A novel in-place recalibration technique partly overcomes this problem through a simple modification of the electronics that permits a scale factor correction. The technique is used to reduce the errors in a commercial system by more than 50 percent up to a temperature of 370 C (700 F). A probe design is proposed to further raise the maximum temperature capability of the measurement system.
This paper discusses the performance of AIRS and examines how it is meeting its operational and research objectives based on the experience of more than 2 yr with AIRS data. We describe the science background and the performance of AIRS in terms of the accuracy and stability of its observed spectral radiances. We examine the validation of the retrieved temperature and water vapor profiles against collocated operational radiosondes, and then we assess the impact thereof on numerical weather forecasting of the assimilation of the AIRS spectra and the retrieved temperature. We close the paper with a discussion on the retrieval of several minor tropospheric constituents from AIRS spectra.
This investigation has been conducted in the Atchafalaya River Basin of South Central Louisiana. This is a humid area of heavily forested swamps with a large volume of flow mostly from a diversion of the lower Mississippi River. Techniques to obtain enlarged imagery from computer compatible tapes of ERTS data without photographic enlargement is explained and illustrated. Techniques of extraction of environmental information from single bands and multiband pattern recognition procedures are explained and evaluated. A comparison of pattern recognition classifications of the Atchafalaya Basin by aircraft multispectral scanner and ERTS MSS data is made. Data for this comparison were gathered within three weeks of each other in the winter of 1973. Scorecards of the accuracy of the classifications are presented. Recommendations are made concerning the utilization of each sensor platform to perform specific tasks of wetlands characterization.
The author has identified the following significant results. The evaluation was conducted in a humid swamp and marsh area of southern Louisiana. ERTS digital multispectral scanner data was compared with similar data gathered by intermediate altitude aircraft. Automatic data processing was applied to several data sets to produce simulated color infrared images, analysis of single bands, thematic maps, and surface classifications. These products were used to determine the effectiveness of satellites to monitor accretion of land, locate aquatic plants, determine water characteristics, and identify marsh and forest species. The results show that to some extent all of these can be done with satellite data. It is most effective for monitoring accretion and least effective in locating aquatic plants. The data sets used show that the ERTS data is superior in mapping quality and accuracy to the aircraft data. However, in some applications requiring high resolution or maximum use of intermittent clear weather conditions, data gathering by aircraft is preferable. Data processing costs for equivalent areas are about three times greater for aircraft data than ERTS data. This is primarily because of the larger volume of data generated by the high resolution aircraft system.
Leaks in the hydrazine supply system of the Shuttle APU can result in hydrazine ignition and fire in the aft compartment of the Shuttle. Indication of the location of a leak could provide valuable information required for operational decisions. WSTF has developed a small, single use sensor for detection of hydrazine leaks. The sensor is composed of a thermistor bead coated with copper(II) oxide (CuO) dispersed in a clay or alumina binder. The CuO-coated thermistor is one of a pair of closely located thermistors, the other being a reference. On exposure to hydrazine the CuO reacts exothermically with the hydrazine and increases the temperature of the coated-thermistor by several degrees. The temperature rise is sensed by a resistive bridge circuit and an alarm registered by data acquisition software. Responses of this sensor to humidity changes, hydrazine concentration, binder characteristics, distance from a liquid leak, and ambient pressure levels as well as application of this sensor concept to other fluids are presented.
The idea for the Students' Cloud Observations OnLine (S'COOL) project as an outreach and education element of NASA's Clouds and the Earth's Radiant Energy System (CERES) research program was conceived in late 1996 during a conversation with a middle school science teacher. S'COOL was implemented in a series of increasingly developed test phases during 1997, as the launch of the first CERES instrument approached. Even before launch, the reception of the project in schools far exceeded expectations. After several delays the first instrument, on the Tropical Rainfall Measuring Mission (TRMM) spacecraft, was launched on Thanksgiving Day, 1997. Since the first launch, development and expansion of the project has continued with expectations for launch of Terra carrying two CERES instruments into a polar orbit in mid-1998. That launch is now expected in fall 1999, and will finally provide overflight of all participating schools. In two years, the project has grown from three initial test participants to over 300 schools now participating in 23 countries on five continents. Students from first grade through university level are involved (most participants are ages 10-15). S'COOL is also being used by a few education professors to teach about Internet use in the classroom. The project continues to grow through word of mouth, presentations at teacher workshops, and now increasingly through teachers who find it during web searches. Participants in the S'COOL project are part of the CERES validation team. They provide ground truth measurements at the time the CERES instrument flies over their location, to be compared with the retrieval of cloud properties by remote sensing from CERES. Quantities reported include cloud type, height, fraction and opacity; information on contrails; surface temperature, pressure and relative humidity; and ground cover (snow/ice, wet, dry; leaves on trees or not). in addition, a comment field on the report form serves as a catch-all for all kinds of interesting observations, including similes written by some classes to describe more exactly the clouds they see. Several not totally unexpected complications with the CERES instrument and processing software mean that the CERES team has not yet reached the point of computing the cloud properties, a high level product at the end of the processing stream. However, progress is being made and we anticipate that we will soon be populating the S'COOL database with a large number of satellite retrievals for comparison with the students' observations. Some satellite retrievals from the initial test phases are already available in the database, The CERES instruments are planned to operate at least through 2006, and the S'COOL Project is planned to continue at least that long, providing motivational learning to as many students as possible. This paper reports on the first several years of the S'CCOL project. It further reports on some of the noteworthy observations and comparisons made possible by this project. Schools are often located in interesting places, in terms of the clouds found there and the satellite's ability to observe these clouds. The paper also reports on the learning opportunities delivered by this project, and on new questions about the planet and its climate which arise in the students' minds as a result of their active participation.
Over the past several years the Pennsylvania Departments of Environmental Protection (DEP), Health (DOH), and Agriculture (PDA) built the GIs-based Pennsylvania West Nile Surveillance System. That system has become a model for collecting data that has a field component, laboratory component, reporting and mapping component, and a public information component. Given the success of the West Nile Virus System and the events of September 11, 2001, DEP then embarked on the development of the Pennsylvania Incident Response System, or PAIRS. PAIRS is an effective GIs-based approach to providing a system for response to incidents of any kind, including terrorism because it is building upon the existing experience, infrastructure and databases that were successfully developed to respond to the West Nile Virus by DEP, DOH, and PDA. The proposed system can be described as one that supports data acquisition, laboratory forensics, decision making/response, and communications. Decision makers will have tools to view and analyze data from various sources and, at the same time, to communicate with the large numbers of people responding to the same incident. Recent collaborations with NASA partners are creating mechanisms for the PAIRS system to incorporate space-based and other remote sensing geophysical parameters relevant to public health assessment and management, such as surface temperatures, precipitation, land cover/land use change, and humidity. This presentation will describe the PAIRS system and outline the Pennsylvania-NASA collaboration for integration of space-based data into the PAIRS system.
Remote sensing observations, such as those from AURA, are necessary to understand the role of cirrus in determining the radiative and humidity budgets of the upper troposphere. Using these measurements quantitatively requires comparisons with in situ measurements that have previously been validated. However, a direct comparison of remote and in situ measurements is difficult due to the requirement that the spatial and temporal overlap be sufficient in order to guarantee that both instruments are measuring the same air parcel. A difficult as this might be for gas phase intercomparisons, cloud inhomogeneities significantly exacerbate the problem for cloud ice water content measurements. The CRYSTAL-FACE mission provided an opportunity to assess how well such intercomparisons can be performed and to establish flight plans that will be necessary for validation of future satellite instruments. During CRYSTAL-FACE, remote and in situ instruments were placed on different aircraft (NASA's ER-2 and WB-59, and the two planes flew in tandem so that the in situ payload flew in the field of view of the remote instruments. We show here that, even with this type of careful flight planning, it is not always possible to guarantee that remote and in situ instruments are viewing the same air parcel. We use ice water data derived from the in situ Harvard Total Water (HV-TW) instrument, and the remote Goddard Cloud Radar System (CRS) and show that agreement between HV-TW and CRS is a strong function of the horizontal separation and the time delay between the aircraft transects. We also use a cloud model to simulate possible trajectories through a cloud and evaluate the use of statistical analysis in determining the agreement between the two instruments. This type of analysis should guide flight planning for future intercomparison efforts, whether for aircraft or satellite-borne instrumentation.
The International Space Station (ISS) now has platforms for conducting research on horticultural plant species under LED lighting, and those capabilities continue to expand. The 'Veggie' vegetable production system was deployed to the ISS as an applied research platform for food production in space. Veggie is capable of growing a wide array of horticultural crops. It was designed for low power usage, low launch mass and stowage volume, and minimal crew time requirements. The Veggie flight hardware consists of a light cap containing red (630 nm), blue, (455 nm) and green (530 nm) LEDs. Interfacing with the light cap is an extendable bellows/baseplate for enclosing the plant canopy. A second large plant growth chamber, the Advanced Plant Habitat (APH), is will fly to the ISS in 2017. APH will be a fully controllable environment for high-quality plant physiological research. APH will control light (quality, level, and timing), temperature, CO2, relative humidity, and irrigation, while scrubbing any cabin or plant-derived ethylene and other volatile organic compounds. Additional capabilities include sensing of leaf temperature and root zone moisture, root zone temperature, and oxygen concentration. The light cap will have red (630 nm), blue (450 nm), green (525 nm), far red (730 nm) and broad spectrum white LEDs (4100K). There will be several internal cameras (visible and IR) to monitor and record plant growth and operations. Veggie and APH are available for research proposals.
The International Space Station (ISS) now has platforms for conducting research on horticultural plant species under LED (Light Emitting Diodes) lighting, and those capabilities continue to expand. The Veggie vegetable production system was deployed to the ISS as an applied research platform for food production in space. Veggie is capable of growing a wide array of horticultural crops. It was designed for low power usage, low launch mass and stowage volume, and minimal crew time requirements. The Veggie flight hardware consists of a light cap containing red (630 nanometers), blue, (455 nanometers) and green (530 nanometers) LEDs. Interfacing with the light cap is an extendable bellowsbaseplate for enclosing the plant canopy. A second large plant growth chamber, the Advanced Plant Habitat (APH), is will fly to the ISS in 2017. APH will be a fully controllable environment for high-quality plant physiological research. APH will control light (quality, level, and timing), temperature, CO2, relative humidity, and irrigation, while scrubbing any cabin or plant-derived ethylene and other volatile organic compounds. Additional capabilities include sensing of leaf temperature and root zone moisture, root zone temperature, and oxygen concentration. The light cap will have red (630 nm), blue (450 nm), green (525 nm), far red (730 nm) and broad spectrum white LEDs (4100K). There will be several internal cameras (visible and IR) to monitor and record plant growth and operations. Veggie and APH are available for research proposals.
Geoscience instrumentation systems are considered along with questions of geoscience environment, signal processing, data processing, and design problems. Instrument platforms are examined, taking into account ground platforms, airborne platforms, ocean platforms, and space platforms. In situ and laboratory sensors described include acoustic wave sensors, age sensors, atmospheric constituent sensors, biological sensors, cloud particle sensors, electric field sensors, electromagnetic field sensors, precision geodetic sensors, gravity sensors, ground constituent sensors, horizon sensors, humidity sensors, ion and electron sensors, magnetic field sensors, tide sensors, and wind sensors. Remote sensors are discussed, giving attention to sensing techniques, acoustic echo-sounders, gamma ray sensors, optical sensors, radar sensors, and microwave radiometric sensors.
Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.
The concept of global climate change encompasses more than merely an alteration in temperature; it also includes spatial and temporal covariations in precipitation and humidity, and more frequent occurrence of extreme weather events. The impact of these variations, which can occur at a variety of temporal and spatial scales, could have a direct impact on disease transmission through their environmental consequences for pathogen, vector, and host survival, as well as indirectly through human demographic and behavioral responses. New and future sensor systems will allow scientists to investigate the relationships between climate change and environmental risk factors at multiple spatial, temporal and spectral scales. Higher spatial resolution will provide better opportunities for mapping urban features previously only possible with high resolution aerial photography. These opportunities include housing quality (e.g., Chagas'disease, leishmaniasis) and urban mosquito habitats (e.g., dengue fever, filariasis, LaCrosse encephalitis). There are or will be many new sensors that have higher spectral resolution, enabling scientists to acquire more information about parameters such as soil moisture, soil type, better vegetation discrimination, and ocean color, to name a few. Although soil moisture content is now detectable using Landsat, the new thermal, shortwave infrared, and radar sensors will be able to provide this information at a variety of scales not achievable using Landsat. Soil moisture could become a key component in transmission risk models for Lyme disease (tick survival), helminthiases (worm habitat), malaria (vector-breeding habitat), and schistosomiasis (snail habitat).
The Atmospheric Infrared Sounder (AIRS) and its two companion instruments (AMSU) and (HSB) are designed to provide atmospheric temperature and humidity profiles with radiosonde accuracty. The performance of AIRS since launch on Aqua has been exceptional indicating that it will meet or exceed its objectives.
Passive microwave remote sensing of the Earth from space provides information essential for understanding the Earth's environment and its evolution. Parameters such as soil moisture, sea surface temperature and salinity, and profiles of atmospheric temperature and humidity are measured at frequencies determined by the physics (e.g. sensitivity to changes in desired parameters) and by the availability of suitable spectrum free from interference. Interference from manmade sources (radio frequency interference) is an impediment that in many cases limits the potential for accurate measurements from space. A review is presented here of the frequencies employed in passive microwave remote sensing of the Earth from space and the associated experience with RFI.