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NASA NTRS2002

An Improved Retrieval of Tropospheric Nitrogen Dioxide from GOME

We present a retrieval of tropospheric nitrogen dioxide (NO2) columns from the Global Ozone Monitoring Experiment (GOME) satellite instrument that improves in several ways over previous retrievals, especially in the accounting of Rayleigh and cloud scattering. Slant columns, which are directly fitted without low-pass filtering or spectral smoothing, are corrected for an artificial offset likely induced by spectral structure on the diffuser plate of the GOME instrument. The stratospheric column is determined from NO2 columns over the remote Pacific Ocean to minimize contamination from tropospheric NO2. The air mass factor (AMF) used to convert slant columns to vertical columns is calculated from the integral of the relative vertical NO2 distribution from a global 3-D model of tropospheric chemistry driven by assimilated meteorological data (Global Earth Observing System (GEOS)-CHEM), weighted by altitude dependent scattering weights computed with a radiative transfer model (Linearized Discrete Ordinate Radiative Transfer), using local surface albedos determined from GOME observations at NO2 wavelengths. The AMF calculation accounts for cloud scattering using cloud fraction, cloud top pressure, and cloud optical thickness from a cloud retrieval algorithm (GOME Cloud Retrieval Algorithm). Over continental regions with high surface emissions, clouds decrease the AMT by 20- 30% relative to clear sky. GOME is almost twice as sensitive to tropospheric NO2 columns over ocean than over land. Comparison of the retrieved tropospheric NO2 columns for July 1996 with GEOS-CHEM values tests both the retrieval and the nitrogen oxide radical (NOx) emissions inventories used in GEOS-CHEM. Retrieved tropospheric NO2 columns over the United States, where NOx emissions are particularly well known, are within 18% of GEOS-CHEM columns and are strongly spatially correlated (r = 0.78, n = 288, p less than 0.005). Retrieved columns show more NO2 than GEOS-CHEM columns over the Transvaal region of South Africa and industrial regions of the northeast United States and Europe. They are lower over Houston, India, eastern Asia, and the biomass burning region of central Africa, possibly because of biases from absorbing aerosols.

Martin, Randall V.↗

NASA NTRSDate not supplied

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗

NASA NTRS1983

Satellite sensing capabilities for surface temperature and meteorological parameters over the ocean

Remote meteorological measurements over the oceans have been used extensively for weather forecasting, ship safety, and global-scale studies of climate and sea conditions. A review is conducted regarding the satellite-sensing capabilities for sea-surface temperature and tropospheric marine meteorological mesurements. The tropospheric measurements are concerned with vertical temperature profiles, integrated water vapor and liquid water, rain, aerosols and surface winds. Attention is also given to several environmental-monitoring applications where satellite sensed synoptic data might be combined with ground and airborne chemical measurements to provide improved assessments of regional and global ennvironmental quality and climatology. Special emphasis is given to current satellite measurement accuracies (errors) and to programs involving U.S. technology. Aspects of sea-surface temperature are treated in detail in connection with extensive studies concentrated in this area.

Darnell, W. L.↗

NASA NTRS2001

Degradation of MODIS Optics and its Reflective Solar Bands Calibration

The MODerate Resolution Imaging Spectroradiometer (MODIS) has 36 spectral bands with wavelength ranging from 0.41 micron to 14.5 micron and spatial resolution between 0.25, 0.5, and 1.0 km at Nadir. Its ProtoFlight Model (PFM) on the NASA EOS Terra spacecraft has been providing global coverage of the Land, Ocean, and Atmosphere for the science community since the instrument opened its Nadir door on 24 February 2000. The MODIS optical system consists of a 2-sided paddle wheel scan mirror, a fold mirror, a primary mirror, and other aft optics. The sensor's 20 reflective solar bands from 0.41 to 2.1 micron are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition to SD, degradation of the MODIS optics in the reflective solar bands has been observed, including variations in degradation between the two sides of the MODIS scan mirror. During MODIS first year of on-orbit operation, the overall degradations at the shortest wavelength (0.41 micron) are about 3% for SD, and in excess of 10% for the MODIS system. In this paper, we will present our degradation analysis results and discuss their impact on the reflective solar bands' on-orbit calibration.

Xiong, X.↗

NASA NTRS1979

Satellite measurements of tropospheric aerosols

Landsat data were originally used to demonstrate that a linear relationship exists between the upwelling visible radiance and the aerosol optical thickness (essentially all of this thickness is in the troposphere) over oceans. Since that time similar relationships have been shown to exist for sensors on the GOES and NOAA-5 satellites. A global scale ground truth experiment using Tiros-N data is planned and will investigate the variability of the linear relationship at different sites around the globe. A comparison of the results for the different satellites is presented, together with a discussion of the requirements for routine satellite monitoring of tropospheric aerosols on a global scale.

Griggs, M.↗

NASA NTRS2009

Chlorophyll Meters Aid Plant Nutrient Management

On December 7, 1972, roughly 5 hours and 6 minutes after launch, the crew of Apollo 17 took one of history s most famous photographs. The brilliant image of the fully illuminated Earth, the African and Antarctic continents peering out from behind swirling clouds, came to be known as the Blue Marble. Today, Earth still sometimes goes by the Blue Marble nickname, but as the satellites comprising NASA s Earth Observing System (EOS) scan the planet daily in ever greater resolutions, it is often the amount of green on the planet that is a focus of researchers attention. Earth s over 400,000 known plant species play essential roles in the planet s health: They absorb carbon dioxide and release the oxygen we breathe, help manage the Earth s temperature by absorbing and reflecting sunlight, provide food and habitats for animals, and offer building materials, medication, and sustenance for humans. As part of NASA s efforts to study our own planet along with the universe around it, the Agency s EOS satellites have been accumulating years of valuable data about Earth s vegetation (not to mention its land features, oceans, and atmosphere) since the first EOS satellite launched in 1997. Among the powerful sensors used is the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra and Aqua satellites. MODIS sweeps the entire Earth every few days, beaming back information gathered across 36 bands of visible and infrared light, yielding images that let scientists track how much of Earth is green over the course of seasons and years. Monitoring the density and distribution of vegetation on Earth provides a means of determining everything from the impact of natural and human-induced climate change to the potential outbreak of disease. (Goddard Space Flight Center and U.S. Department of Defense researchers have determined, for example, that vegetation density can be used to pinpoint regions of heavy rainfall in Africa regions ripe for outbreaks of rainfall-correlated diseases like mosquito-borne Rift Valley fever.) While the Space Agency is continually seeking to upgrade the power and scope of its satellite sensors, it is also finding ways to bring that potent information-gathering capacity down to Earth. Scientists at Stennis Space Center developed one such tool that is placing some of those sensor capabilities in the hands of farmers and agricultural researchers on the ground.

Source record↗

NASA NTRS2013

Global Light System for JEM-EUSO

The Global Light System (GLS) is a network of ground-based Xenon flash lamps and steered UV lasers to validate the key functions of the JEM-EUSO instrument. These functions include triggering efficiency, the accuracy of intrinsic luminosity measurements, and the reconstructed pointing direction accuracy. GLS units will generate benchmark optical signatures in the atmosphere with similar characteristics to the optical signals of cosmic ray EASs. The lasers will generate tracks and the flashers will generate point flashes. But unlike air showers, the number, energy, precise time, direction (lasers) can be specified. JEM-EUSO will reconstruct the pointing directions of the lasers and the energy of the lasers and flash lamps to monitor the detector's triggers, and accuracy of energy and direction reconstruction. 12 GLS units will be deployed at selected sites around the globe. The JEM-EUSO footprint will pass over a GLS unit on average once per (near) moonless night under clear conditions for appropriately selected sites. The 12 units will be supplemented by campaign style measurements with an airborne unit that will be flown over the open ocean at selected altitudes under JEM-EUSO. A GLS prototype in an airplane will support a high-altitude balloon flight in 2014 of a proto-type JEM-EUSO telescope. We will describe the concept and system design and report on the status of prototyping and the selection process for candidates sites.

Christl, Mark↗

NASA NTRS2014

Carbon Monitoring System Flux Estimation and Attribution: Impact of ACOS-GOSAT X(CO2) Sampling on the Inference of Terrestrial Biospheric Sources and Sinks

Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite 'IBUKI' (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (X(CO2)) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is approx.1132 for 1-yr of the 74 055 GOSAT X(CO2) observations, which indicates that GOSAT provides approx.1132 independent pieces of information about surface fluxes. We quantify the impact of GOSAT's spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.

biased sampling↗

NASA NTRS1990

Remote sensing of the biosphere; Proceedings of the Meeting, Orlando, FL, Apr. 19, 20, 1990

The global context and monitoring of the biological aspects relevant to the EOS program are addressed, the large-scale regional field experiments required to understand ecosystem functioning in more detail and to calibrate the application of remote-sensing techniques for extracting flux and state information are covered, and sensors of the proposed EOS platform are discussed. Attention is given to terrestrial productivity, both tropical-forest and semiarid environments, coastal environments, and global oceanic productivity. Focus is placed on the First International Field Experiment (FIFE) in Kansas, the HAPEX field experiment in France, the ABLE-2 experiment in the Amazon, and the Forest Ecosystem Study in Maine. The proposed electro-optical instruments for EOS including both MODIS-N and MODIS-T, the AIRS and MISR instruments, the ITIR, and ERBE calibration issues are considered.

Smith, James A.↗

NASA NTRS1998

Variability of Arctic Sea Ice as Viewed from Space

Over the past 20 years, satellite passive-microwave radiometry has provided a marvelous means for obtaining information about the variability of the Arctic sea ice cover and particularly about sea ice concentrations (% areal coverages) and from them ice extents and the lengths of the sea ice season. This ability derives from the sharp contrast between the microwave emissions of sea ice versus liquid water and allows routine monitoring of the vast Arctic sea ice cover, which typically varies in extent from a minimum of about 8,000,000 sq km in September to a maximum of about 15,000,000 sq km in March, the latter value being over 1.5 times the area of either the United States or Canada. The vast Arctic ice cover has many impacts, including hindering heat, mass, and y momentum exchanges between the oceans and the atmosphere, reducing the amount of solar radiation absorbed at the Earth's surface, affecting freshwater transports and ocean circulation, and serving as a vital surface for many species of polar animals. These direct impacts also lead to indirect impacts, including effects on local and perhaps global atmospheric temperatures, effects that are being examined in general circulation modeling studies, where preliminary results indicate that changes on the order of a few percent sea ice concentration can lead to temperature changes of 1 K or greater even in local areas outside of the sea ice region. Satellite passive-microwave data for November 1978 through December 1996 reveal marked regional and interannual variabilities in both the ice extents and the lengths of the sea ice season, as well as some statistically significant trends. For the north polar ice cover as a whole, maximum ice extents varied over a range of 14,700,000 - 15,900,000 km(2), while individual regions showed much greater percentage variations, e.g., with the Greenland Sea experiencing a range of 740,000 - 1,1110,000 km(2) in its yearly maximum ice coverage. Although variations from year to year and region to region are large, overall the Arctic ice extents did show a statistically significant, 2.8%/ decade negative trend over the 18.2-year period. Ice season lengths, which vary from only a few weeks near the ice margins to the full year in the large region of perennial ice coverage, also experienced interannual variability, and mapping their trends allows detailed geographic information on exactly where the ice season lengthened and where it shortened. Over the 18 years, ice season lengthening occurred predominantly in the western hemisphere and was strongest in the western Labrador Sea, while ice season shortening occurred predominantly in the eastern hemisphere and was strongest in the eastern Barents Sea. Much information about other important Arctic sea ice variables has also been obtained from satellite data, including information about melt ponding, temperature, snow cover, and ice velocities. For instance, maps of ice velocities have now been made from satellite scatterometry data, including information about melt ponding, temperature, snow cover, and ice velocities.

Parkinson, Claire L.↗

NASA NTRS2000

Changes in the Areal Extent of Arctic Sea Ice: Observations from Satellites

Wintertime sea ice covers 15 million square kilometers of the north polar region, an area exceeding one and a half times the area of the U. S. Even at the end of the summer melt season, sea ice still covers 7 million square kilometers. This vast ice cover is an integral component of the climate system, being moved around by winds and waves, restricting heat and other exchanges between the ocean and atmosphere, reflecting most of the solar radiation incident on it, transporting cold, relatively fresh water equatorward, and affecting the overturning of ocean waters underneath, with impacts that can be felt worldwide. Sea ice also is a major factor in the Arctic ecosystem, affecting life forms ranging from minute organisms living within the ice, sometimes to the tune of millions in a single ice floe, to large marine mammals like walruses that rely on sea ice as a platform for resting, foraging, social interaction, and breeding. Since 1978, satellite technology has allowed the monitoring of the vast Arctic sea ice cover on a routine basis. The satellite observations reveal that, overall, the areal extent of Arctic sea ice has been decreasing since 1978, at an average rate of 2.7% per decade through the end of 1998. Through 1998, the greatest rates of decrease occurred in the Seas of Okhotsk and Japan and the Kara and Barents Seas, with most other regions of the Arctic also experiencing ice extent decreases. The two regions experiencing ice extent increases over this time period were the Bering Sea and the Gulf of St. Lawrence. Furthermore, the satellite data reveal that the sea ice season shortened by over 25 days per decade in the central Sea of Okhotsk and the eastern Barents Sea, and by lesser amounts throughout much of the rest of the Arctic seasonal sea ice region, although not in the Bering Sea or the Gulf of St. Lawrence. Concern has been raised that if the trends toward shortened sea ice seasons and lesser sea ice coverage continue, this could entail major consequences to the polar climate and to the lifestyles (and perhaps even the survivability) of polar bears and other polar species.

Parkinson, Claire L.↗

NASA NTRS2011

Assessment of Nutritional Intake During Space Flight and Space Flight Analogs

Background: Maintaining adequate nutrient intake in microgravity is important not only to meet health maintenance needs of astronauts but also to help counteract the negative effects of space flight. Beyond this, food provides psychosocial benefits throughout a mission. Objective: The purpose of this presentation is to discuss dietary intake data from multiple space programs, including Space Shuttle and the International Space Station. Description: These data arise from medical monitoring of both dietary intake and crew health, as well as research protocols designed to assess the role of diet in counteracting bone loss and other health concerns. Ground-based studies are conducted to better understand some of the negative issues related to space flight. Examples of these analog studies are extended bed rest studies, vitamin D supplementation studies in Antarctica, and saturation diving missions on the floor of the ocean. Methods and findings will be presented describing the use of weighed records, diet diaries, and food frequency questionnaires in these various environments. Provision of food and nutrients in spaceflight is important for many body systems including cardiovascular, musculoskeletal, endocrine, immune, and others. Some key areas of concern are loss of body mass, bone and muscle loss, radiation exposure, nutrient intakes during spacewalks, depletion of nutrient stores, and inadequate dietary intake. Initial experimental research studies using food and nutrition as a countermeasure to aid in mitigating these concerns are underway. Conclusion: Beyond their importance for the few individuals leaving the planet, these studies have significant implications for those remaining on Earth.

Rice, Barbara L.↗

NASA NTRS2011

Observation of Hydrological Processes Using Remote Sensing: Volume 2: The Science of Hydrology - Chapter 2.14

Improving water management can make a significant contribution to achieving most of the Millennium Development Goals established by the UN General Assembly in 2000, especially those related to poverty, hunger, and major diseases. The World Summit on Sustainable Development (WSSD) in 2002 recognized this need. Water and sanitation in particular received great attention from the Summit. The Johannesburg Plan of Implementation recommended to improve water resources management and scientific understanding of the water cycle through joint cooperation and research. For this purpose, it is recommended to promote knowledge sharing, provide capacity building, and facilitate the transfer of technology including remote-sensing (RS) and satellite technologies, especially to developing countries and countries with economies in transition, and to support these countries in their efforts to monitor and assess the quantity and quality of water resources, for example, by establishing and/or further developing national monitoring networks and water resources databases and by developing relevant national indicators. The Johannesburg Plan also adopted integrated water resources management as the overarching concept in addressing and solving water-related issues. As a result of the commitments made in the Johannesburg Plan of Implementation, several global and regional initiatives have emerged. Current international initiatives such as the Global Monitoring for Environment and Security (GMES) program of the European Commission and the European Space Agency (ESA), and the Global Earth Observation System of Systems (GEOSS) 10-Year Implementation Plan, have all identified Earth observation (EO) of the water cycle as the key in helping to solve the world s water problems. The availability of spatial information on water quantity and quality will also enable closure of the water budget at river basin and continental scales to the point where effective water management is essential (e.g., as requested by the European Union s Water Framework Directive (WFD), as well as national policies). Geo-information science and EO are vital in achieving a better understanding of the water cycle and better monitoring, analysis, prediction, and management of the world s water resources. The major components of the water cycle of the Earth system and their possible observations are presented. Such observations are essential to understand the global water cycle and its variability, both spatially and temporally, and can only be achieved consistently by means of EOs. Additionally, such observations are essential to advance our understanding of coupling between the terrestrial, atmospheric, and oceanic branches of the water cycle, and how this coupling may influence climate variability and predictability. Water resources management directly interferes with the natural water cycle in the forms of building dams, reservoirs, water transfer systems, and irrigation systems that divert and redistribute part of the water storages and fluxes on land. The water cycle is mainly driven and coupled to the energy cycle in terms of phase changes of water (changes among liquid, water vapor, and solid phases) and transport of water by winds in addition to gravity and diffusion processes. The water-cycle components can be observed with in situ sensors as well as airborne and satellite sensors in terms of radiative quantities. Processing and conversion of these radiative signals are necessary to retrieve the water-cycle components.

Wilder, Peter↗

NASA NTRS2023

Soil Moisture and Sea Surface Salinity Derived from Satellite-Borne Sensors

The monitoring of soil moisture and sea surface salinity over the Earth has been profoundly enhanced during the last thirteen years owing to new generation of satellite sensors. L-band radiometry is currently the only technology providing direct measurements of soil moisture, insensitive to surface roughness and distribution of elements in the soil, and the only technology that allows to measure sea surface salinity from space. The SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active Passive) satellite missions resolve global and local variability with a spatial resolution of approximately 43 km, a swath width close to 1000 km, and a sampling time, for each mission, of at least twice every 3 days. These resolutions and samplings can be increased by either merging data from the two sensors, and with complementary informations gathered with other passive or active sensors, or with in situ information at higher spatial resolution. Numerous scientific studies based on the use of this new type of measurement have led to a better understanding and constraint of the processes governing the variability of the water cycle, ocean circulation and the Earth's climate. The continuity of measurements, and the increased spatial and radiometric resolution is critical for fulfilling scientific needs. Future L-band radiometry missions currently being planned in Europe (the Copernicus Imaging Microwave Radiometer), and in China (the Ocean Salinity Mission) should provide better constraint on auxiliary parameters by combining multiple frequencies, but they will not have improved spatial resolution beyond SMOS and SMAP. The temporal continuity with SMOS and SMAP will most likely not be ensured. In parallel, new concepts are being developed to increase spatial resolution of both land and ocean parameters.

J. Boutin↗

NASA NTRS2011

Biogeochemical Impact of Long-Range Transported Dust over Northern South China Sea

Transpacific transport and impact of Asian dust aerosols have been well documented (e.g., results from ACE-Asia and regional follow-on campaigns), but little is known about dust invasion to the South China Sea (SCS). On 19-21 March 2010, a fierce Asian dust storm affected large areas from the Gobi deserts to the West Pacific, including Taiwan and Hong Kong. As a pilot study of the 7-SEAS (Seven South East Asian Studies) in the northern SCS, detailed characteristics of long-range transported dust aerosols were first observed by a comprehensive set of ground-based instruments deployed at the Dongsha islands (20deg42'52" N, 116deg43'51" E). Aerosol measurements such as particle mass concentrations, size distribution, optical properties, hygroscopicity, and vertical profiles help illustrate the evolution of this dust outbreak. Our results indicate that these dust particles were mixed with anthropogenic and marine aerosols, and transported near the surface. Satellite assessment of biogeochemical impact of dust deposition into open oceans is hindered by our current inability in retrieving areal dust properties and ocean colors over an extensive period of time, particularly under the influence of cloudy conditions. In this paper, we analyze the changes of retrieved Chlorophyll-a (Chl-a) concentration over the northern SCS, considered as oligotophic waters in the spring, from long-term SeaWiFS measurements since 1997. Over the past decade, six long-range transported dust events are identified based on spatiotemporal evolutions of PM10 measurements from regional monitoring stations, with the aid of trajectory analysis. Multi-year composites of Chl-a imagery for dust event and non-dust background during March-April are applied to overcome insufficient retrievals of Chl-a due to cloudy environment. Due to anthropogenic modification within a shallow boundary layer off the densely populated and industrial southeast coast of China, the iron ion activation of deliquescent dust particles enhances the efficiency of fertilization for biological productivity. Compared to the West Pacific, the marine ecosystem in the northern SCS is much more susceptible to the biogeochemical impact of long-range transported Asian dust.

Tsay, Si-Chee↗

NASA NTRS1993

1993 Earth Observing System reference handbook

Mission to Planet Earth (MTPE) is a NASA-sponsored concept that uses space- and ground-based measurement systems to provide the scientific basis for understanding global change. The space-based components of MTPE will provide a constellation of satellites to monitor the Earth from space. Sustained observations will allow researchers to monitor climate variables overtime to determine trends; however, space-based monitoring alone is not sufficient. A comprehensive data and information system, a community of scientists performing research with the data acquired, and extensive ground campaigns are all important components. Brief descriptions of the various elements that comprise the overall mission are provided. The Earth Observing System (EOS) - a series of polar-orbiting and low-inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans - is the centerpiece of MTPE. The elements comprising the EOS mission are described in detail.

Asrar, Ghassem↗

NASA NTRS1993

A Look at a Day of Data from the TOPEX/POSEIDON GPS Receiver

On August 10, 1992, the Topex/Poseidon Satellite was launched into orbit about the Earth to begin its mission to chart the oceans' topography. One of the instruments on board this satellite is a receiver for tracking the navigational satellites of the NAVSTAR Global Positioning System (GPS). The purpose of the receiver is to provide the data required to enable a demonstration of continuous sub-decimeter level positioning of Topex/Poseidon using the GPS. This discussion will briefly describe the data and then focus on the special statistical tools used to pre-process and monitor the large quantity of navigational data. It will be shown how robust regression splines provide useful models and residual diagnostics for the task. Numerous specialized graphics will be presented to show how the data are monitored in a daily operational environment.

robust regression spline statistical graphics↗

NASA NTRS2011

MODIS Radiometric Calibration and Uncertainty Assessment

Since launch, Terra and Aqua MODIS have collected more than II and 9 years of datasets for comprehensive studies of the Earth's land, ocean, and atmospheric properties. MODIS observations are made in 36 spectral bands: 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, MODIS was developed with very stringent calibration and uncertainty requirements. As a result, MODIS was designed and built with a set of state of the art on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated if necessary. In terms of its calibration traceability, MODIS RSB calibration is reflectance based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of MODIS calibration methodologies and discusses details of its on-orbit calibration uncertainties. It assesses uncertainty contributions from individual components and differences between Terra and Aqua MODIS due to their design characteristics and on-orbit periormance. Also discussed in this paper is the use of MODIS LIB uncertainty index CUI) product.

Xiong, Xiaoxiong↗