Academic literature on the topic 'Atmospheric data collection using satellites'
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Journal articles on the topic "Atmospheric data collection using satellites"
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Sporre, Moa K., Ewan J. O'Connor, Nina Håkansson, Anke Thoss, Erik Swietlicki, and Tuukka Petäjä. "Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland." Atmospheric Measurement Techniques 9, no. 7 (July 21, 2016): 3193–203. http://dx.doi.org/10.5194/amt-9-3193-2016.
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Abstract. Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). MODIS collection 6 overestimated LWP by on average 13 g m−2 (11 %). Interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.
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Gopal, Banala Krishna. "Atmospheric Data Collecting Cubesat using Raspberry PI." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 3880–88. http://dx.doi.org/10.22214/ijraset.2021.35848.
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As advances in technology make payloads and instruments for space missions smaller, lighter, and more power efficient, a distinct segment market is emerging for low-cost missions on very small spacecrafts such as - micro, nano, and picosatellites. Due to the fact that even after many technological advances the usage of miniature satellites the remote sensing of atmospheric is still not a widely explored aspect, to overcome this we idealized a system to build a CUBESAT which can be built with minimal efforts. We proposed this system with an objective to build a CUBESAT to detect different weather aspects of our earth at the troposphere layer which is the lowest layer of earth. We implemented our project using the Raspberry Pi due to its versatility in multi-processing and connectivity. Here the Raspberry-Pi is going to be configured with transceiver modules in the CUBESAT’s sender-end to gather atmospheric data associated with temperature, gasses present, humidity and pressure using CUBESAT sensors and after the reception of data at ground station by Arduino configured as receiver, data is going to be stored in an accessible website for viewing and further computations.
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da Silva, Áurea Aparecida, Wilson Yamaguti, Hélio Koiti Kuga, and Cláudia Celeste Celestino. "Assessment of the Ionospheric and Tropospheric Effects in Location Errors of Data Collection Platforms in Equatorial Region during High and Low Solar Activity Periods." Mathematical Problems in Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/734280.
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The geographical locations of data collection platforms (DCP) in the Brazilian Environmental Data Collection System are obtained by processing Doppler shift measurements between satellites and DCP. When the signals travel from a DCP to a satellite crossing the terrestrial atmosphere, they are affected by the atmosphere layers, which generate a delay in the signal propagation, and cause errors in its final location coordinates computation. The signal propagation delay due to the atmospheric effects consists, essentially, of the ionospheric and tropospheric effects. This work provides an assessment of ionospheric effects using IRI and IONEX models and tropospheric delay compensation using climatic data provided by National Climatic Data Center. Two selected DCPs were used in this study in conjunction with SCD-2 satellite during high and low solar activity periods. Results show that the ionospheric effects on transmission delays are significant (about hundreds of meters) in equatorial region and should be considered to reduce DCP location errors, mainly in high solar activity periods, while in those due to tropospheric effects the zenith errors are about threemeters. Therefore it is shown that the platform location errors can be reduced when the ionospheric and tropospheric effects are properly considered.
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Kalukin, Andrew, Satoshi Endo, Russell Crook, Manoj Mahajan, Robert Fennimore, Alice Cialella, Laurie Gregory, Shinjae Yoo, Wei Xu, and Daniel Cisek. "Image Collection Simulation Using High-Resolution Atmospheric Modeling." Remote Sensing 12, no. 19 (October 1, 2020): 3214. http://dx.doi.org/10.3390/rs12193214.
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A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.
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Catchpole, Ivan, Peter Upton, Andrew Sinclair, and Jim Nagle. "Wide Area Differential GPS Field Study." Journal of Navigation 47, no. 2 (May 1994): 146–58. http://dx.doi.org/10.1017/s0373463300012066.
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Inmarsat commissioned the field study to be carried out by Signal Computing Ltd. in association with the Royal Greenwich Observatory. The study aimed to identify the commercial suitability of Wide Area Differential GPS (WADGPS) corrections. The corrections provided to users will be relayed via Inmarsat-3 geostationary satellites and are required to be valid over the footprint of an entire Inmarsat ocean region (approximately one third of the Earth's surface).The study has been conducted within the Inmarsat Atlantic Ocean Region East. Trials took place over a five-month period to achieve a representative set of data. Six widely-distributed collection sites were used to ensure that the maximum duration of satellite data were received and that a representative model for atmospheric effects was obtained. Analysis is restricted to the use of GPS carrier and phase data obtained using the C/A code transmitted by Block II satellites only.This paper presents the analysis of data collected during a four-day trial period. The ability to determine the GPS satellite ephemeris (independent of GPS broadcast ephemeris), Klobuchar model parameters tailored to the oceanic region, and satellite clock corrections using GPS data obtained from this limited deployment of collection sites is addressed. The primary degradation effects on stand-alone GPS positioning of Selective Availability (SA) are corrected using WADGPS, resulting in a significant improvement in position accuracy.
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Liu, Yuling, Yunyue Yu, Peng Yu, Heshun Wang, and Yuhan Rao. "Enterprise LST Algorithm Development and Its Evaluation with NOAA 20 Data." Remote Sensing 11, no. 17 (August 24, 2019): 2003. http://dx.doi.org/10.3390/rs11172003.
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Satellite land surface temperatures (LSTs) have been routinely produced for decades from a variety of polar-orbiting and geostationary satellites, which makes it possible to generate LST climate data globally. However, consistency of the satellite LSTs from different satellite missions is a concern for such purpose; an enterprise satellite LST algorithm is desired for the LST production through different satellite missions, or at the least, through series satellites of a satellite mission. The enterprise LST algorithm employs the split window technique and uses the emissivity explicitly in its formula. This research focuses on the enterprise LST algorithm design, development and its evaluations with the National Oceanic and Atmospheric Administration’s (NOAA) 20 (N20) Visible Infrared Imaging Radiometer Suite (VIIRS) data available since 5 January 2018. In this study, the enterprise LST algorithm was evaluated using simulation dataset consisting of over 2000 profiles from SeeBor collection and the results show a bias of 0.19 K and 0.34 K and standard deviation of 0.48 K and 0.69 K for nighttime and daytime, respectively. The in situ observations from seven NOAA Surface Radiation budget (SURFRAD) sites and two Baseline Surface Radiation Network (BSRN) sites were used for LST validation. The results indicate a bias of −0.3 K and a root mean square error (RMSE) of 2.06 K for SURFRAD stations and a bias of 0.2 K and a RMSE of ~2 K for BSRN sites. Further, the cross-satellite analysis presents a bias of 0.7 K and an RMSE of 1.9 K for comparisons with AQUA MODIS LST (MYD11_L2, Collection 6). The enterprise N20 VIIRS LST product reached the provisional maturity in February 2019 and is ready for users to use in their applications.
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Sutlieff, Gary, Lucy Berthoud, and Mark Stinchcombe. "Using Satellite Data for CBRN (Chemical, Biological, Radiological, and Nuclear) Threat Detection, Monitoring, and Modelling." Surveys in Geophysics 42, no. 3 (April 17, 2021): 727–55. http://dx.doi.org/10.1007/s10712-021-09637-5.
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Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field
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Tate, PM. "Monthly mean surface thermal structure in the Tasman Sea from satellite imagery, 1979-84." Marine and Freshwater Research 39, no. 5 (1988): 579. http://dx.doi.org/10.1071/mf9880579.
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The use of satellite data provides a far greater density and more uniform distribution of observations than the more classical modes of oceanographic data collection. By sacrificing some spatial resolution of the satellite data, it is possible to retrieve sea surface temperatures on a global basis that have absolute accuracies within 1�C of drifting buoy data. Five years of low resolution infra-red data from the United States' National Oceanic and Atmospheric Administration satellites have been analysed for the area of the Tasman and Southern Coral Seas. Monthly mean surface thermal patterns compare favourably with previous studies using Merchant Ship data. In the western Tasman Sea the East Australian Current can be clearly seen throughout the year, although the more transitory eddies often associated with the current system are not apparent. General circulation patterns off the west coast of the South Island of New Zealand show severe bending of the isotherms to the south. The nature of the surface thermal signal of the Tasman Front is quite different either side of the Lord Howe Rise and there is some doubt whether these two features are linked.
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Li, Ruibo, Hua Li, Lin Sun, Yikun Yang, Tian Hu, Zunjian Bian, Biao Cao, Yongming Du, and Qinhuo Liu. "An Operational Split-Window Algorithm for Retrieving Land Surface Temperature from Geostationary Satellite Data: A Case Study on Himawari-8 AHI Data." Remote Sensing 12, no. 16 (August 13, 2020): 2613. http://dx.doi.org/10.3390/rs12162613.
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An operational split-window (SW) algorithm was developed to retrieve high-temporal-resolution land surface temperature (LST) from global geostationary (GEO) satellite data. First, the MODTRAN 5.2 and SeeBor V5.0 atmospheric profiles were used to establish a simulation database to derive the SW algorithm coefficients for GEO satellites. Then, the dynamic land surface emissivities (LSEs) in the two SW bands were estimated using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED), fractional vegetation cover (FVC), and snow cover products. Here, the proposed SW algorithm was applied to Himawari-8 Advanced Himawari Imager (AHI) observations. LST estimates were retrieved in January, April, July, and October 2016, and three validation methods were used to evaluate the LST retrievals, including the temperature-based (T-based) method, radiance-based (R-based) method, and intercomparison method. The in situ night-time observations from two Heihe Watershed Allied Telemetry Experimental Research (HiWATER) sites and four Terrestrial Ecosystem Research Network (TERN) OzFlux sites were used in the T-based validation, where a mean bias of −0.70 K and a mean root-mean-square error (RMSE) of 2.29 K were achieved. In the R-based validation, the biases were 0.14 and −0.13 K and RMSEs were 0.83 and 0.86 K for the daytime and nighttime, respectively, over four forest sites, four desert sites, and two inland water sites. Additionally, the AHI LST estimates were compared with the Collection 6 MYD11_L2 and MYD21_L2 LST products over southeastern China and the Australian continent, and the results indicated that the AHI LST was more consistent with the MYD21 LST and was generally higher than the MYD11 LST. The pronounced discrepancy between the AHI and MYD11 LST could be mainly caused by the differences in the emissivities used. We conclude that the developed SW algorithm is of high accuracy and shows promise in producing LST data with global coverage using observations from a constellation of GEO satellites.
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Williams, Dean N., V. Balaji, Luca Cinquini, Sébastien Denvil, Daniel Duffy, Ben Evans, Robert Ferraro, Rose Hansen, Michael Lautenschlager, and Claire Trenham. "A Global Repository for Planet-Sized Experiments and Observations." Bulletin of the American Meteorological Society 97, no. 5 (May 1, 2016): 803–16. http://dx.doi.org/10.1175/bams-d-15-00132.1.
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Abstract Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.
Dissertations / Theses on the topic "Atmospheric data collection using satellites"
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McNally, A. P. "Satellite sounding of tropospheric temperature and humidity." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276585.
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Alston, Erica J. "Aerosol characterization in the Southeastern U. S. using satellite data for applications to air quality and climate." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43589.
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Tropospheric aerosol information from NASA satellites in space has reached the milestone of ten years of continuous measurements. These higher resolution satellite aerosol records allow for a broader regional perspective than can be gained using only sparsely located ground based monitoring sites. Decadal satellite aerosol data have the potential to advance knowledge of the climatic impacts of aerosols through better understanding of solar dimming/brightening and radiative forcings on regional scales, as well as aid in air quality applications. The goal of this thesis is to develop and implement methodologies for using satellite remotely sensed data in conjunction with ground based observations and modeling for characterization of regional aerosol variations with applications to air quality and climate studies in the Southeastern U. S. This region is of special interest because of distinct aerosol types, less warming climate trends compared to the rest of U.S., and growing population.
To support this primary goal, a technique is developed that exploits the statistical relationship between PM2.5 (particulate matter that has an aerodynamic radius of 2.5 µm or less) and satellite AOD (Aerosol Optical Depth) from MODIS (Moderate resolution Imaging Spectroradiometer) where a probabilistic approach is used for air quality assessments in the metropolitan Atlanta area. The metropolitan Atlanta area experiences the poorest air quality during the warmer seasons. We found that satellite AODs capture a significant portion of PM2.5 concentration variability during the warmer months of the year with correlation values above 0.5 for a majority of co-located (in time and space) ground based PM2.5 monitors, which is significant at the 95% confidence interval. The developed probabilistic approach uses five years of satellite AOD, PM2.5 and their related AQI (Air Quality Index) to predict future AQI based solely on AOD retrievals through the use of AOD thresholds, e.g., 80% of Code Green AQI days have AOD below 0.3. This approach has broad applicability for concerned stakeholders in that it allows for quick dissemination of pertinent air quality data in near-real time around a satellite overpass.
Examination of the use of multiple satellite sensors to aid in investigating the impacts of biomass burning in the region is performed. The utility of data fusion is evaluated in understanding the effects of the large wildfire that burned in May 2007.
This wildfire caused PM2.5 in the metropolitan Atlanta area to exceed healthy levels with some measurements surpassing 150 µg/m3 during the month. OMI (Ozone Monitoring Instrument) AI (Aerosol Index), which qualitatively measures absorbing aerosols, have high values of more than 1.5 during May 26 - 31, 2007. CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) a space based lidar was used to determine the vertical structure of the atmosphere across the region during the active fire period. CALIPSO was able to identify wildfire aerosols both within the planetary boundary layer (likely affects local air quality) and aloft where aerosol transport occurs. This has important implications for climatic studies specifically aerosol radiative effects.
In-depth analysis of the satellite and ground based aerosol data records over the past decade (2000 - 2009) are performed from a climatic perspective. The long temporal scale allowed for better characterization of seasonality, interannual variability, and trends. Spatial analysis of ten years of AOD from both MODIS and MISR (Multi-angle Imaging Spectroradiometer) showed little variability of AOD during the winter with mean AOD below 0.1 for the entire region, while the summer had decidedly more variability with mean AOD around 0.33 for MODIS and 0.3 for MISR. Seasonal analysis of the PM2.5 revealed that summer means are twice as high as winter means for PM2.5. All of the datasets show interannual variability that suggests with time AOD and PM2.5 are decreasing, but seasonal variability obscured the detection of any appreciable trends in AOD; however, once the seasonal influence was removed through the creation of monthly anomalies there were decreasing trends in AOD, but only MODIS had a trend of -0.00434 (per month) that statistically significant at the 95% confidence level.
Satellite and ground-based data are used to assess the radiative impacts of aerosols in the region. The regional TOA (Top Of the Atmosphere) direct radiative forcing is estimated by utilizing satellite AOD from MODIS and MISR both on Terra, along with satellite derived cloud fraction, surface albedo (both from MODIS), and single scattering albedo (SSA) from MISR data from 2000 - 2009. Estimated TOA forcing varied from between -6 to -3 W/m2 during the winter, and during the warmer months there is more variation with ΔF varying between -28 to -12.6 W/m2 for MODIS and -26 to -11 W/m2 for MISR. The results suggest that when AOD, cloud fraction and surface albedo are all consider they add an additional 6 W/m2 of TOA forcing compared to TOA forcing due to aerosol effects only. Varying SSA can create changes in TOA forcing of about 5 W/m2. With removal of the seasonal variability timeseries anomaly trend analysis revealed that estimated TOA forcing is decreasing (becoming less negative) with MODIS based estimates statistically significant at the 95% confidence level.
Optical and radiative 1-D radiative transfer modeling is performed to assess the daily mean TOA forcing and forcing at the surface for representative urban and background aerosol mixtures for summer and winter. During the winter, modeled TOA forcing is -2.8 and -5 W/m2 for the WB and WU cases, and the modeled summer TOA forcings (SB = -13.3 W/m2) also generally agree with earlier estimates. While surface forcings varied from -3 to -210 W/m2. The radiative forcing efficiency at the TOA (amount of forcing per unit of AOD at 550 nm) varied from -9 to -72 W/m2 τ-1, and RFE at the surface varied from -50 to -410 W/m2 τ-1. It was found that the forcing efficiency for biomass burning aerosols are similar to the forcing efficiency of background aerosols during the summer that highlights the importance of possible increased biomass burning activity. Ultimately, the methodologies developed in this work can be implemented by the remote sensing community and have direct applicability for society as a whole.
Books on the topic "Atmospheric data collection using satellites"
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Chesters, Dennis. An atlas of upper tropospheric radiances observed in the 6 to 7 micrometer water vapor band using TOVS data from the NOAA weather satellites during 1979-1991. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1992.
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Atmospheric Research and Exposure Assessment Laboratory (U.S.), ed. On the feasibility of using satellite derived data to infer surface-layer ozone concentration patterns: Project summary. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Research and Exposure Assessment Laboratory, 1994.
Find full textBook chapters on the topic "Atmospheric data collection using satellites"
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Madankan, Reza, Puneet Singla, and Tarunraj Singh. "Parameter Estimation of Atmospheric Release Incidents Using Maximal Information Collection." In Dynamic Data-Driven Environmental Systems Science, 310–21. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25138-7_28.
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Hadria, Rachid, Loubna El Mansouri, Tarik Benabdelouhab, and Pietro Ceccato. "Geospatial Technics, Modelling, Meteorological, and Ground Data for Crop Management in Semi-Arid Zones of Morocco." In Geospatial Technologies for Effective Land Governance, 107–23. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5939-9.ch007.
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Recent geospatial technologies offer an infinite number of opportunities in the domain of land management and governance. This is due principally to the fact that new satellites allow the collection and monitoring of important information about soil, crops, weather, and climate. In this context, this chapter presents a review of studies conducted in three semi-arid plains in Morocco during the last two decades on the combined use of geospatial technologies, modelling tools, meteorological, and ground data to manage irrigated lands in semi-arid zones. The three studied regions are located in three different sites well distributed over the country. This chapter presents a simple and clear summary of what has been performed using geospatial technologies by Moroccan researchers to improve agricultural management in irrigated areas in Morocco. Such work could help policymakers in developing efficient land governance policies by taking into account the latest scientific results.
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Dolman, Han. "The Hydrological Cycle and Climate." In Biogeochemical Cycles and Climate, 105–28. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198779308.003.0008.
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Water is a key part of the Earth system and interacts with climate through a variety of mechanisms. The chapter initially describes the effect of atmospheric moisture on the lapse rate and then discusses cloud formation and the main global reservoirs and fluxes, including precipitation, and discharge into the oceans. Atmospheric transport of water vapour, together with its relation to precipitation, is then discussed. It is shown that meridional transport can occur with a few very strong events, through atmospheric rivers. The difference between evaporation over the ocean and that over land is shown, with the help of data from Earth observation satellites, and the recycling of water is shown to depend very much on locality. Finally, the importance of frozen water on climate is described, using the recent decrease in Arctic sea ice, and the variability in ice sheet extent and consequent sea levels during the Last Glacial Maximum.
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Quattrochi, Dale A., and Stephen J. Walsh. "Remote Sensing." In Geography in America at the Dawn of the 21st Century. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780198233923.003.0037.
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As noted in the first edition of Geography in America, the term “remote sensing” was coined in the early 1960s by geographers to describe the process of obtaining data by use of both photographic and nonphotographic instruments (Gaile and Wilmot 1989: 46). Although this is still a working definition today, a more explicit and updated definition as it relates to geography can be phrased as: “remote sensing is the science, art, and technology of identifying, characterizing, measuring, and mapping of Earth surface, and near Earth surface phenomena from some position above using photographic or nonphotographic instruments.” Both patterns and processes may be the object of investigation using remote sensing data. The science dimension of geographic remote sensing is rooted in the fact that: (1) it is dealing with primary data, wherein the investigator must have an understanding of the environmental phenomena under scrutiny, and (2) the investigator must understand something of the physics of the energy involved in the sensing instrument and the atmospheric pathway through which the energy passes from the energy source, to the Earth object, to the sensor. The art dimension of geographic remote sensing has to do with the creative ways that the scientific interpretations are presented for visualization and measurement. The technological dimension of geographic remote sensing has to do with the constantly evolving hardware, software, and algorithmic manipulation and modeling involved in the collection, processing, and interpreting of data regarding the Earth phenomena under investigation. It is the rapidly advancing combination of these three dimensions over recent decades that has brought remote sensing to be a vibrant and dynamic part of the discipline of geography today. We wish not to dwell at length on the historical aspects of remote sensing as it relates to geography. This has been done quite adequately in the first edition of Geography in America as well as in other publications, such as the American Society of Photogrammetry and Remote Sensing (ASPRS) Manual of Remote Sensing series (e.g. Colwell 1983), that is now going through a third edition and complete update, and is being presented as a compendium of individual volumes that deal with specific aspects of remote sensing science.
Conference papers on the topic "Atmospheric data collection using satellites"
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Fang, Russell J. F., Mustafa Eroz, and Neal Becker. "Data collection and SCADA over GEO-MSS satellites using Spread SCMA." In 2009 International Workshop on Satellite and Space Communications (IWSSC). IEEE, 2009. http://dx.doi.org/10.1109/iwssc.2009.5286301.
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Ren, Yuan, and Jinjun Shan. "Calibration of Atmospheric Density Model Using Orbital Data of Multiple Satellites." In AIAA Guidance, Navigation, and Control Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-0345.
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SUMMERS, ROBERT. "Balloon system data collection and telemetry using Low Earth Orbit light satellites (Lightsats)." In International Balloon Technology Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-3685.
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De Silva, Shelton G. "Knowledge of Arctic and EQQ Unmanned Aerial Vehicles for Multiple Applications." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-11477.
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The rapid change in climate conditions, and the present demand for political and commercial interest in the Arctic region will cause considerable implications on the environment, ecosystem, security, and on the social system in the region. Today, governments, scientists and researchers understand that there is a huge gap of knowledge in the Arctic region and this must be addressed prior to development of the region, or there will be devastating environmental consequences in the future. Existing studies concluded by various organizations including Lloyd’s of London, US Geological Survey and other institutes emphasize that in order to ensure sustainable development in the Arctic, it is important to close the existing gap of knowledge by obtaining accurate scientific data, and make available this data to scientists, researchers and policy makers, for them to take sound decisions on both Arctic challenges and future economic opportunities. The scientists understand that existing lack of knowledge is mainly due to insufficient information in the Arctic and the inability to obtain sufficient scientific data to understand the Arctic region in-depth. Main challenges will be, the vast area of the Arctic, inaccessibility to complex and remote areas, long cold dark winters and short summers, rapid changes of weather conditions etc. Presently, existing satellites provide extremely valuable scientific data, however scientists emphasize that this data would be further analyzed (due to inaccuracy) and collaborated with data on actual close observations, physical sea–ice samples, ice core samples, data from surface and bottom of the sea-ice, glacial ice etc. Collecting data from high altitudes using Unmanned Aerial Vehicles are not new to the Arctic region, and have been used for number of years. The AMAP, (Arctic Monitoring and Assessment Program Workshop), Oslo October, 2008, recommended that it is of great importance that scientists use unmanned aerial vehicles in the Arctic to obtain important environment measurements. Further, added to the AMAP work plan for 2011–2013, is to develop safety guidelines and cross-jurisdictional flight pilot projects, to demonstrate the use of unmanned aerial service (UAS) in the Arctic Environmental Monitoring Plan. The Canadian Government also completed the feasibility study to build a “High Arctic Research Station” in the high north to serve the entire world, for scientists to have an opportunity to share data and support the knowledge for researchers to conclude their investigations. The government is further considering purchasing, three large high-altitude Global Hawk drones for Arctic surveillance, and seeking small snowmobiles and remote control aircrafts to monitor the extreme complex landscape of the Arctic. At present, there is no method to obtain accurate surface and atmospheric data in complex and remote areas, and this requirement has become the highest priority and should be addressed urgently. In order to obtain sufficient accurate data from the Arctic surface and atmosphere, EQQUERA Inc. innovated, is designing and developing multipurpose, multifunctional SG EQQ Unmanned Aerial Vehicles that are able to access remote and complex areas in the Arctic, and operate in challengeable weather conditions such as cold long dark nights.
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Janajreh, Isam, Rana Qudaih, Ilham Talab, and Zaki Al Nahari. "Atmospheric Wind Data Collection and Wind Turbine Analysis in UAE." In ASME 2009 3rd International Conference on Energy Sustainability collocated with the Heat Transfer and InterPACK09 Conferences. ASMEDC, 2009. http://dx.doi.org/10.1115/es2009-90288.
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Wind turbine technology has improved dramatically in the last two decades as demonstrated by their plummeting capital costs ($0.08/KW), the enhanced reliability, and the increased efficiency. Large-scale wind turbines and wind farms provided 94.1GW of electrical grid capacity in 2007, and are expected to reach 160 GW by 2010 according to WWEA. Wind energy is plentiful and sustainable energy source with an estimated potential capacity of 72 TW. In Denmark the inland and offshore implementation of wind energy generation adds 1/5 of their electrical grid capacity. In Germany, it is forecasted to attain 12.5% by early 2010. Offshore wind farms have lower ecological impact due to lack of land mortgage, easier transportation, and low perception of noise issue. In the gulf region, the generated power can fulfill the power needs of UAE’s islands, while the excess capacity can be channeled to the inland grids fulfilling the peak demand. In this work we will investigate the implementation of low-turning moment wind turbines in the UAE, suited for low wind speeds (∼3–5m/s) and that consists of two research components: (i) Collection of wind data, analysis, recommendation for implementation strategies, and using Masdar wind data to assess its characteristics and its fit for wind turbine implementation; (ii) Carry out flow analysis on a downwind, two-bladed, horizontal-axes wind turbine to investigate the flow lift, drag and wake characteristics on the tower blade interaction. The interaction is studied utilizing Arbitrary Lagrangian Eulerian method. Downwind turbines are self-aligned, pass up yaw mechanisms and its needed power, and have fewer moving parts that necessitate regular maintenance. These factors however play in favor of wind turbine that is subjected to low wind speed.
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Azzouz, Salim, Johnny Blevins, Tyler Thomas, Makenzie Johnson, Clarke O’Connor, Nchetachukwu C. Anih, Melanie Ronoh, Ernuel Tonge, and Cykelle Semper. "Data Collection and Analysis Using a Wind Turbine and a Photovoltaic Solar Panel." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11751.
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Abstract A weather data collection study is currently conducted using a renewable energy training system. The system is composed of a LabVolt trainer, two sun tracking photovoltaic solar panels and a small wind turbine. The LabVolt training system is located in one of the McCoy School of Engineering laboratories, the solar panels and the wind turbine are located in the neighborhood of the Engineering building at Midwestern State University in Wichita Falls, Texas. A set of meteorological data collecting outdoor sensors to monitor the impact of weather conditions on the power generation of the sun-tracking photovoltaic solar panels and the wind turbine have been installed on the building roof. Weather parameters such as atmospheric temperature, pressure, humidity, and rainfall are monitored using a Davis Vantage Pro 2 data collecting system. A number of LabVIEW data acquisition cards and signal processing modules are used to monitor the sun-tracking photovoltaic solar panels’ output voltage, the wind turbine output voltage, the atmospheric temperature, the solar irradiance, and the wind direction, speed, and RPM. A voltage divider has been built to step down the 90V DC voltage produced by the solar panels to 12V DC voltage required for the trainer electrical circuits. A LabVIEW data processing program is used to create instantaneous graphic displays of the collected data on a monitoring screen. The LabVolt trainer is equipped with two charge controller electronic devices, one is used for the sun tracking photovoltaic solar panels, and one is used for the wind turbine. They are used to control the flow of electrical energy through a set of electrical loading devices and a set of storages batteries. Additionally, the LabVolt trainer is equipped with two kilowatt-hour-meters counting the electrical energy consumed by the electrical loads. The trainer is also equipped with two inverters transforming the 12 V DC voltage collected from both energy producing devices to 120 V that can be used by the electrical loading devices. A brief description of all used electronic components and devices is provided in the paper, as well a detailed experiment set-up with a procedure to run them. The project has been divided into three consecutive phases. The first phase dealt with connecting the solar panels, wind turbine, and data collecting sensors to the LabVIEW data acquisition software. The second phase is currently dealing with setting up the trainer solar and wind electricity providing circuits. In the third upcoming phase, it is expected that the data collected by the sensors will be gradually archived using Excel files and analyzed for weather data correlation purposes. It is also expected that the training system will be used to teach upcoming mechanical engineering students about how to set up an independent renewable energy system and the necessary equipment required to run it.
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Bernardin, John D., Snezana Konecni, and Roger Wiens. "Design and Testing of a Prototype Atmospheric Gas Collection Apparatus for a Mission to Mars." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14499.
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A novel spacecraft, the Sample Collection for Investigation of Mars (SCIM), was proposed for the collection and return of atmospheric gas and dust samples from the martian atmosphere. The SCIM mission, part of NASA's Mars Exploration Strategy, would allow scientists to greatly enhance our understanding of Mars' water, climate, and geological evolution by studying the element and isotopic composition of the gas and dust. The SCIM spacecraft was proposed to collect its samples during a single high-speed pass through the martian atmosphere at an altitude of 37 km and return the samples back to earth. For the atmospheric gas sampling aspect the SCIM employs the Atmospheric Collection Experiment (ACE), a dual-component apparatus consisting of a passive and a cryogenic sorption gas collection system. Each of these systems possesses a collection vessel that is initially under high vacuum. At the time of entry into the martian atmosphere, valves on SCIM open and gas flows into the parallel-plumbed passive and cryogenic sorption gas collection systems. The passive system simply allows the incoming gas to fill an initially evacuated 1 Liter vessel. The cryogenic sorption system employs a Joule-Thompson cryocooler and sorption medium that initially condenses and captures the incoming gas. As the SCIM begins to exit the atmosphere isolation valves close and trap the gas samples in their collection systems for the return journey back to earth. The minimum SCIM mission goal was to collect 100 cm3 @STP(≈ 0.2 g) of martian atmospheric gas and the ACE was being designed to gather 1000 cm3 @STP (≈ 2.0 g) using both the passive and cryogenic systems. The volumes referred to above correspond to standard temperature and pressure on Earth (e.g., STP). The goals of this study were to prove the gas collection concepts mentioned above and develop the numerical and experimental tools to allow for the optimization of a flight worthy ACE. This paper discusses the design, analysis, and testing of a prototype ACE. First, more specific details on the design and testing methodology for the prototype are presented. Next, the development of a computational fluid dynamics (CFD) model is discussed. Finally, empirical pressure data from the prototype tests are used to assess the performances of the passive and cryogenic sorption gas collection systems and are compared to numerical pressure predictions to provide a benchmark for the CFD model. Results indicate that the prototype ACE is capable of meeting the design goal of 1000 cm3 @STP (2.0 g) of total gas collection.
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Sindoni, Giampiero, Claudio Paris, Cristian Vendittozzi, Erricos C. Pavlis, Ignazio Ciufolini, and Antonio Paolozzi. "The Contribution of LARES to Global Climate Change Studies With Geodetic Satellites." In ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/smasis2015-8924.
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Satellite Laser Ranging (SLR) makes an important contribution to Earth science providing the most accurate measurement of the long-wavelength components of Earth’s gravity field, including their temporal variations. Furthermore, SLR data along with those from the other three geometric space techniques, Very Long Baseline Interferometry (VLBI), Global Navigation Satellite Systems (GNSS) and DORIS, generate and maintain the International Terrestrial Reference Frame (ITRF) that is used as a reference by all Earth Observing systems and beyond. As a result we obtain accurate station positions and linear velocities, a manifestation of tectonic plate movements important in earthquake studies and in geophysics in general. The “geodetic” satellites used in SLR are passive spheres characterized by very high density, with little else than gravity perturbing their orbits. As a result they define a very stable reference frame, defining primarily and uniquely the origin of the ITRF, and in equal shares, its scale. The ITRF is indeed used as “the” standard to which we can compare regional, GNSS-derived and alternate frames. The melting of global icecaps, ocean and atmospheric circulation, sea-level change, hydrological and internal Earth-mass redistribution are nowadays monitored using satellites. The observations and products of these missions are geolocated and referenced using the ITRF. This allows scientists to splice together records from various missions sometimes several years apart, to generate useful records for monitoring geophysical processes over several decades. The exchange of angular momentum between the atmosphere and solid Earth for example is measured and can be exploited for monitoring global change. LARES, an Italian Space Agency (ASI) satellite, is the latest geodetic satellite placed in orbit. Its main contribution is in the area of geodesy and the definition of the ITRF in particular and this presentation will discuss the improvements it will make in the aforementioned areas.
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Rasheed, Adil, Mandar Tabib, and Jørn Kristiansen. "Wind Farm Modeling in a Realistic Environment Using a Multiscale Approach." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61686.
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We present a multiscale approach to model a windfarm under real meteorological conditions. The multiscale model consists of a mesoscale atmospheric code coupled to a stochastic ocean wave model, a microscale model and a super-microscale model. The mesoscale model (with 2.5km × 2.5km horizontal resolution) forces the microscale model (with finer 100m × 100m horizontal resolution). The microscale model is capable of resolving surface variations both on wavy and complex terrain surfaces. Finally, the computed wind, temperature and turbulent kinetic energy from microscale model are used to provide boundary conditions to a super-microscale model, which has features to resolve turbine wakes using actuator line model. The three classes of models are validated using a very diverse array of observational data obtained from satellites, radiosondes and a wind tunnel. Towards the end, performance of an operational onshore wind farm under realistic meteorological conditions is evaluated.
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Goldstein, Neil, Brian Gregor, Jamine Lee, Stephen K. Kramer, Stuart Kozola, and Kenneth J. Semega. "IR Structured Emission-Based Speciation, Thermometry, and Tomography of CO and H2O in High-Pressure Combustors." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90899.
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Passive optical probes and high-resolution emission spectroscopy are used to provide a general-purpose real-time temperature and chemical species sensing capability. Probes can be inserted in the combustor, at the turbine inlet, in the augmenter, or at the engine exit with application as an engine development diagnostic tool that provides spatially resolved measurements of the key combustion parameters: temperature, CO concentration, and H2O concentration. Multiple probes are arrayed to collect the emitted infrared radiation over different views of the hot gas path. Line-of-sight averaged concentrations and temperatures are determined by spectral analysis of the emitted radiation along each line of sight (LOS). Spatial profiles may also be determined by simultaneous analysis of overlapping lines of sight. The collected infrared spectra contain optically thin and optically thick features that reflect the effects of emission and absorption within the combustion region. The known spectral structure of the component spectra can be used for the automated interpretation of the observed radiance spectra in terms of concentrations and temperatures along the line of sight, and in specific volume elements of overlapping lines of sight. In this work, we present measurements of atmospheric-pressure flames and high-pressure combustors and describe the formalism for fitting the observed spectra to a basis of simulated spectra to extract estimates of concentrations and temperatures. The spectral basis is constructed using a multilayer radiation transport model, in which each line-of-sight or measurement volume is divided into segments of uniform concentration and temperature. The observed radiance emanating from each segment is calculated as a function of the local physical variables. The collection of observed data, which contains a highly structured emission spectrum over each line of sight, is fit to the spectral basis to extract line-of-sight averaged physical properties, or in the case of spatial reconstruction, volume-averaged properties for each of the overlap regions.
Reports on the topic "Atmospheric data collection using satellites"
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Rathinam, Francis, P. Thissen, and M. Gaarder. Using big data for impact evaluations. Centre of Excellence for Development Impact and Learning (CEDIL), February 2021. http://dx.doi.org/10.51744/cmb2.
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The amount of big data available has exploded with recent innovations in satellites, sensors, mobile devices, call detail records, social media applications, and digital business records. Big data offers great potential for examining whether programmes and policies work, particularly in contexts where traditional methods of data collection are challenging. During pandemics, conflicts, and humanitarian emergency situations, data collection can be challenging or even impossible. This CEDIL Methods Brief takes a step-by-step, practical approach to guide researchers designing impact evaluations based on big data. This brief is based on the CEDIL Methods Working Paper on ‘Using big data for evaluating development outcomes: a systematic map’.