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NASA NTRS2011

Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

Fensholt, R.↗
NASA NTRS2005

Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth-orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops, and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop-production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without the need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multiyear crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Lepoutre, Damien↗
NASA NTRS2011

Initial Results from On-Orbit Testing of the Fram Memory Test Experiment on the Fastsat Micro-Satellite

The Memory Test Experiment is a space test of a ferroelectric memory device on a low Earth orbit satellite that launched in November 2010. The memory device being tested is a commercial Ramtron Inc. 512K memory device. The circuit was designed into the satellite avionics and is not used to control the satellite. The test consists of writing and reading data with the ferroelectric based memory device. Any errors are detected and are stored on board the satellite. The data is sent to the ground through telemetry once a day. Analysis of the data can determine the kind of error that was found and will lead to a better understanding of the effects of space radiation on memory systems. The test is one of the first flight demonstrations of ferroelectric memory in a near polar orbit which allows testing in a varied radiation environment. The initial data from the test is presented. This paper details the goals and purpose of this experiment as well as the development process. The process for analyzing the data to gain the maximum understanding of the performance of the ferroelectric memory device is detailed.

MacLeond, Todd C.↗
NASA NTRS2011

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via satellite is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and satellite data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). In the current project MODIS data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability over large regions. Hence the use of satellite data is critical to observe Juniperus spp. pollen phenology. MODIS data was used to observe Juniperus spp. pollen phenology. The MODIS surface reflectance product(MOD09) provided information on the Juniper spp. cone formation and cone density (Fig 1). Ground based observational records of pollen release timing and quantities were used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS.

Luvall, J. C.↗
NASA NTRS2010

Synergy of Satellite-Surface Observations for Studying the Properties of Absorbing Aerosols in Asia

Through interaction with clouds and alteration of the Earth's radiation budget, atmospheric aerosols significantly influence our weather and climate. Monsoon rainfalls, for example, sustain the livelihood of more than half of the world's population. Thus, understanding the mechanism that drives the water cycle and freshwater distribution is high-lighted as one of the major near-term goals in NASA's Earth Science Enterprise Strategy. Every cloud droplet/ice-crystal that serves as an essential element in portraying water cycle and distributing freshwater contains atmospheric aerosols at its core. In addition, the spatial and temporal variability of atmospheric aerosol properties is complex due to their dynamic nature. In fact, the predictability of the tropical climate system is much reduced during the boreal spring, which is associated with the peak season of biomass burning activities and regional/long-range transport of dust aerosols. Therefore, to accurately assess the impact of absorbing aerosols on regional-to-global climate requires not only modeling efforts but also continuous observations from satellites, aircraft, networks of ground-based instruments and dedicated field experiments. Since 1997 NASA has been successfully launching a series of satellites the Earth Observing System - to intensively study, and gain a better understanding of, the Earth as an integrated system. Through participation in many satellite remote-sensing/retrieval and validation projects over the years, we have gradually developed and refined the SMART (Surface-sensing Measurements for Atmospheric Radiative Transfer) and COMMIT (Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile observatories, a suite of surface remote sensing and in-situ instruments that proved to be vital in providing high temporal measurements, which complement the satellite observations. In this talk, we will present SMART-COMMIT which has played key roles, serving as network or supersite, in major international research projects such as the Joint Aerosol Monsoon Experiment (JAM EX), a core element of the Asian Monsoon Years (AMY, 2008-2012). SMART-COMMIT deployments during 2008 AMY/JAMEX were conducted in northwestern China to characterize the properties of dust-laden aerosols and in the vicinity of Beijing for mega-city aerosols. In 2009, SMART-COMMIT also participated in the JAMEX/RAJO-MEGHA (Radiation, Aerosol Joint Observations-Monsoon Experiment in the Gangetic-Himalayan Area; Sanskrit for Dust-Cloud) to study the aerosol properties, solar absorption and the associated atmospheric warming, and the climatic impact of elevated aerosols during the pre-monsoon season in South Asia. We will show results from these field experiments, as well as discuss a new initiative of 7-SEAS (7 South East Asian Studies) to study the interaction of anthropogenic aerosols with regional meteorology, particularly with clouds.

Tsay, Si-Chee↗
NASA NTRS2012

Search for Dark Matter Satellites Using the Fermi-Lat

Numerical simulations based on the ACDM model of cosmology predict a large number of as yet unobserved Galactic dark matter satellites. We report the results of a Large Area Telescope (LAT) search for these satellites via the gamma-ray emission expected from the annihilation of weakly interacting massive particle (WIMP) dark matter. Some dark matter satellites are expected to have hard gamma-ray spectra, finite angular extents, and a lack of counterparts at other wavelengths. We sought to identify LAT sources with these characteristics, focusing on gamma-ray spectra consistent with WIMP annihilation through the bb(sup raised bar) channel. We found no viable dark matter satellite candidates using one year of data, and we present a framework for interpreting this result in the context of numerical simulations to constrain the velocity-averaged annihilation cross section for a conventional 100 Ge V WIMP annihilating through the bb(sup raised bar) channel.

Ackermann, M.↗
NASA NTRS2012

Field and Satellite Observations of the Formation and Distribution of Arctic Atmospheric Bromine Above a Rejuvenated Sea Ice Cover

Recent drastic reduction of the older perennial sea ice in the Arctic Ocean has resulted in a vast expansion of younger and saltier seasonal sea ice. This increase in the salinity of the overall ice cover could impact tropospheric chemical processes. Springtime perennial ice extent in 2008 and 2009 broke the half-century record minimum in 2007 by about one million km2. In both years seasonal ice was dominant across the Beaufort Sea extending to the Amundsen Gulf, where significant field and satellite observations of sea ice, temperature, and atmospheric chemicals have been made. Measurements at the site of the Canadian Coast Guard Ship Amundsen ice breaker in the Amundsen Gulf showed events of increased bromine monoxide (BrO), coupled with decreases of ozone (O3) and gaseous elemental mercury (GEM), during cold periods in March 2008. The timing of the main event of BrO, O3, and GEM changes was found to be consistent with BrO observed by satellites over an extensive area around the site. Furthermore, satellite sensors detected a doubling of atmospheric BrO in a vortex associated with a spiral rising air pattern. In spring 2009, excessive and widespread bromine explosions occurred in the same region while the regional air temperature was low and the extent of perennial ice was significantly reduced compared to the case in 2008. Using satellite observations together with a Rising-Air-Parcel model, we discover a topographic control on BrO distribution such that the Alaskan North Slope and the Canadian Shield region were exposed to elevated BrO, whereas the surrounding mountains isolated the Alaskan interior from bromine intrusion.

Nghiem, Son V.↗
NASA NTRS2012

The Strengths and Limitations of Satellite Data for Evaluating Tropospheric Processes in Chemistry-Climate Models

There is now a wealth of satellite data products available with which to evaluate a model fs simulation of tropospheric composition and other model processes. All of these data products have their strengths and limitations that need to be considered for this purpose. For example, uncertainties are introduced into a data product when 1) converting a slant column to a vertical column and 2) estimating the amount of a total column of a trace gas (e.g., ozone, nitrogen dioxide) that resides in the troposphere. Oftentimes, these uncertainties are not well quantified and the satellite data products are not well evaluated against in situ observations. However, these limitations do not preclude us from using these data products to evaluate our model processes if we understand these strengths and limitations when developing diagnostics. I will show several examples of how satellite data products are being used to evaluate particular model processes with a focus on the strengths and limitations of these data products. In addition, I will introduce the goals of a newly formed team to address issues on the topic of "satellite data for improved model evaluation and process studies" that is established in support of the IGAC/SPARC Global Chemistry ]Climate Modeling and Evaluation Workshop.

Duncan, Bryan↗
NASA NTRS2010

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗
NASA NTRS2012

The Effects of Climate Variability on Phytoplankton Composition in the Equatorial Pacific Ocean using a Model and a Satellite-Derived Approach

Compared the interannual variation in diatoms, cyanobacteria, coccolithophores and chlorophytes from the NASA Ocean Biogeochemical Model with those derived from satellite data (Hirata et al. 2011) between 1998 and 2006 in the Equatorial Pacific. Using NOBM, La Ni a events were characterized by an increase in diatoms (correlation with MEI, r=-0.81, P<0.05), while cyanobacteria concentrations decreased significantly (r=0.61; P<0.05). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. This represented a radical shift in the phytoplankton community in response to climate variability. However, satellite-derived phytoplankton groups were all negatively correlated with climate variability (r ranged from -0.39 for diatoms to -0.64 for coccolithophores, P<0.05). Spatially, the satellite-derived approach was closer to an independent in situ dataset for all phytoplankton groups except diatoms than NOBM. However, the different responses of phytoplankton to intense interannual events in the Equatorial Pacific raises questions about the representation of phytoplankton dynamics in models and algorithms: is a phytoplankton community shift as in the model or an across-the-board change in abundances of all phytoplankton as in the satellite-derived approach.

Rousseaux, C. S.↗
NASA NTRS2012

Using Satellites to Investigate the Sensitivity of Longwave Downward Radiation to Water Vapor at High Elevations

Many studies suggest that high-elevation regions may be among the most sensitive to future climate change. However, in situ observations in these often remote locations are too sparse to determine the feedbacks responsible for enhanced warming rates. One of these feedbacks is associated with the sensitivity of longwave downward radiation (LDR) to changes in water vapor, with the sensitivity being particularly large in many high-elevation regions where the average water vapor is often low. We show that satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) can be used to expand the current ground-based observational database and that the monthly averaged clear-sky satellite estimates of humidity and LDR are in good agreement with the well-instrumented Center for Snow and Avalanche Studies ground-based site in the southwestern Colorado Rocky Mountains. The relationship between MODIS-retrieved precipitable water vapor and surface specific humidity across the contiguous United States was found to be similar to that previously found for the Alps. More important, we show that satellites capture the nonlinear relationship between LDR and water vapor and confirm that LDR is especially sensitive to changes in water vapor at high elevations in several midlatitude mountain ranges. Because the global population depends on adequate fresh water, much of which has its source in high mountains, it is critically important to understand how climate will change there. We demonstrate that satellites can be used to investigate these feedbacks in high-elevation regions where the coverage of surface-based observations is insufficient to do so.

Naud, Catherine M.↗
NASA NTRS2011

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces peop Ie indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be tran sported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over brightreflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as Sea WiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from Sea WiFS and MODISlike instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Hsu, N. Christina↗
NASA NTRS2012

Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry

Satellite retrievals of snow depth and water equivalent (SWE) are critical for monitoring watershed scale processes around the world. However, the problem is especially challenging in mountainous regions where complex heterogeneities limit the utility of low resolution satellite sensors. The Geoscience Laser Altimeter Sensor (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat) collected surface elevation data along near-repeat reference transects over land areas from 2003-2009. Although intended for monitoring ice caps and sea ice, the seven year global GLAS data base has provided unprecedented opportunity to test the capability of satellite lidar technology for estimating snow depth over land. GLAS single track and low repeat frequency does not provide data sufficient for operational estimates. However, its comparatively small footprint size of -65 m and its database of seasonal repeat observations during both snow and no-snow conditions have been sufficient to evaluate the potential of spacebased lidar altimetry for estimating snow depth. Recent analysis of ICESat elevations in the Uinta Mountains in NE Utah provide encouraging results for watershed scale estimates of snow depth. Research reported here focuses on the sensitivity of several versions of an ICESat snow depth algorithm to a range of landscape types defined by vegetation cover, slope and roughness. Results are compared to available SNOTEL data.

Jasinski, Michael F.↗
NASA NTRS2011

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Dubovik, O↗
NASA NTRS2012

Short-Term Prediction Research and Transition (SPoRT) Center: Transitioning Satellite Data to Operations

The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

Zavodsky, Bradley↗
NASA NTRS2012

Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

Ichoku, Charles↗
NASA NTRS2012

Fast, Affordable, Science and Technology Satellite (FASTSAT) Huntsville-01 (HSV-01) Spacecraft Lessons Learned Report

The Fast Affordable Science and Technology Satellite (FASTSAT) project is a path finding effort to produce reliable satellite busses for different applications at an unprecedented speed and low cost. The project is designed to be a generational project and the first satellite produced is the Huntsville -01 (HSV-01) spacecraft. The subject of this report is the lessons learned gained during the development, testing, and up to the delivery of the FASTSAT HSV -01 spacecraft. The purpose of this report is to capture the major findings that will greatly benefit the future FASTSAT satellites and perhaps other projects interested in pushing the boundaries for cost and schedule. The FASTSAT HSV -01 primary objectives, success criteria, and team partners are summarized to give a frame of reference to the lessons learned.

Smith, Timothy A.↗
NASA NTRS2012

Alternating Magnetic Field Forces for Satellite Formation Flying

Selected future space missions, such as large aperture telescopes and multi-component interferometers, will require the precise positioning of a number of isolated satellites, yet many of the suggested approaches for providing satellites positioning forces have serious limitations. In this paper we propose a new approach, capable of providing both position and orientation forces, that resolves or alleviates many of these problems. We show that by using alternating fields and currents that finely-controlled forces can be induced on the satellites, which can be individually selected through frequency allocation. We also show, through analysis and experiment, that near field operation is feasible and can provide sufficient force and the necessary degrees of freedom to accurately position and orient small satellites relative to one another. In particular, the case of a telescope with a large number of free mirrors is developed to provide an example of the concept. We. also discuss the far field extension of this concept.

Youngquist, Robert C.↗