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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Results and Lessons from MODIS Thermal Emissive Bands Calibration: Pre-launch to On-orbit

MODIS is a major instrument for the NASA EOS Terra (launched in December 1999) and Aqua (launched in May 2002) missions. It was designed and built to enhance and extend its heritage sensors' measurements and data records with applications covering a wide range of studies of the Earth's land, oceans, and atmosphere. Its 16 thermal emissive bands (TEB), each with 10 detectors, are located on the two cold focal plane assemblies (FPAs) controlled by a passive radiative cooler. Because of instrument design complexity and stringent calibration requirements, extensive calibration and characterization activities were conducted pre-launch by the sensor vendor for both Terra and Aqua MODIS. For TEB, these activities include characterization of detectors' noise and non-linearity and evaluation of their radiometric performance in thermal vacuum at difference instrument temperatures and FPA temperatures. In addition TEB system level response versus scan-angle (RVS) and relative spectral response (RSR) were characterized. MODIS TEB radiometric calibration transfer from pre-launch to on-orbit was performed using spectral bands' responses to the instrument on-board blackbody and a laboratory blackbody calibration source (BCS) traceable to NIST standards. This paper provides a summary of MODIS TEB pre-launch and on-orbit calibration and characterization activities, challenges, data analysis results, and lessons learned with focus on sensors' radiometric performance. A comparison between Terra and Aqua MODIS TEB performance is also presented. A similar summary for the reflective solar bands (RSB) is reported in a separate paper in these proceedings.

Xiong, X.↗
NASA NTRS2017

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

There are many flare forecasting models. For an excellent review and comparison of some of them see Barnes et al. (2016). All these models are successful to some degree, but there is a need for better models. We claim the most successful models explicitly or implicitly base their forecasts on various estimates of components of the photospheric current density J, based on observations of the photospheric magnetic field B. However, none of the models we are aware of compute the complete J. We seek to develop a better model based on computing the complete photospheric J. Initial results from this model are presented in this talk. We present a data driven, near photospheric, 3 D, non-force free magnetohydrodynamic (MHD) model that computes time series of the total J, and associated resistive heating rate in each pixel at the photosphere in the neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of B measured by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series of B in every AR pixel. Errors in B due to these periods can be significant.

Goodman, Michael L.↗
NASA NTRS2013

Italy INAF Analysis Center Report

This report summarizes the activity of the Italian INAF VLBI Analysis Center. Our Analysis Center is located in Bologna, Italy and belongs to the Institute of Radioastronomy, which is part of the National Institute of Astrophysics. IRA runs the observatories of Medicina and Noto, where two 32-m VLBI AZ-EL telescopes are situated. This report contains the AC's VLBI data analysis activities and shortly outlines the investigations into the co-locations of space geodetic instruments.

Negusini, M.↗
NASA NTRS1995

A Mars Rover Mission Simulation on Kilauea Volcano

A field experiment to simulate a rover mission on Mars was performed using the Russian Marsokhod rover deployed on Kilauea Volcano HI in February, 1995. A Russian Marsokhod rover chassis was equipped with American avionics equipment, stereo cameras on a pan and tilt platform, a digital high resolution body-mounted camera, and a manipulator arm on which was mounted a camera with a close-up lens. The six wheeled rover is 2 meters long and has a mass of 120 kg. The imaging system was designed to simulate that used on the planned "Mars Together" mission. The rover was deployed on Kilauea Volcano HI and operated from NASA Ames by a team of planetary geologists and exobiologists. Two modes of mission operations were simulated for three days each: (1) long time delay, low data bandwidth (simulating a Mars mission), and (2) live video, wide-bandwidth data (allowing active control simulating a Lunar rover mission or a Mars rover mission controlled from on or near the Martian surface). Simulated descent images (aerial photographs) were used to plan traverses to address a detailed set of science questions. The actual route taken was determined by the science team and the traverse path was frequently changed in response to the data acquired and to unforeseen operational issues. Traverses were thereby optimized to efficiently answer scientific questions. During the Mars simulation, the rover traversed a distance of 800 m. Based on the time delay between Earth and Mars, we estimate that the same operation would have taken 30 days to perform on Mars. This paper will describe the mission simulation and make recommendations about incorporating rovers into the Mars surveyor program.

Stoker, Carol↗
NASA NTRS2016

Global Carbon Budget 2016

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere the global carbon budget is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1(sigma), reflecting the current capacity to characterize the annual estimates of each component of the global carbon budget. For the last decade available (2006-2015), EFF was 9.3+/-0.5 GtC/yr, ELUC 1.0+/-0.5 GtC/yr,GATM 4.5+/-0.1 GtC/yr, SOCEAN 2.6+/-0.5 GtC/yr, and SLAND 3.1+/-0.9 GtC/yr. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9+/-0.5 GtC/yr, showing a slowdown in growth of these emissions compared to the average growth of 1.8/yr that took place during 2006-2015.Also, for 2015, ELUC was 1.3+/-0.5 GtC/yr, GATM was 6.3+/-0.2 GtC/yr, SOCEAN was 3.0+/-0.5 GtC/yr, and SLAND was 1.9+/-0.9 GtC/yr. GATM was higher in 2015 compared to the past decade (2006-2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4+/-0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2% (range of -1.0 to +1.8% ) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Nino conditions of 2015-2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565+/-55 GtC (2075+/-205 GtCO2) for 1870-2016, about 75% from EFF and 25% from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set.

Quéré, Corinne Le↗
NASA NTRS2010

Application of Satellite Observations to Manage Natural Disasters in the Lake Victoria Basin

Lake Victoria, the second largest fresh water lake in the Eastern part of Africa is a vital natural resource for the economic well being and prosperity of over 30 million people located in riparian regions of Uganda, Kenya and Tanzania. It covers a large area of about 68,870 km2 and produces a GDP of about US $30 billion per year. The region is also very much prone to natural disasters such as severe floods during heavy precipitation periods in the Eastern part of Africa. In addition to floods, the precipitation also produces large infestations of mosquito larvae due to the standing water in many areas. This further causes multiple vector borne diseases such as Malaria, Rift Valley Fever and more. These problems are of serious concern and require active and aggressive surveillance and management to minimize the loss of human and animal lives and property damage. Satellite imagery and observations along with the in situ measurements provide a great tool to analyze and study this area and inform the policy makers to make calculated policy decisions which are more beneficial to the environment. Recently, NASA and USAID have joined forces with the Regional Center for Mapping of Resources for Development (RCMRD) located in Nairobi, Kenya to utilize multiple NASA sensors such as TRMM, SRTM and MODIS to develop flood potential maps for the Lake Victoria Basin. The idea is to generate a flood forecasts and "nowcasts" that can be sent to the disaster management organizations of Uganda, Kenya, and Tanzania. Post flood event satellite imagery is becoming a common tool to assess the areas inundated by flooding. However, this work is unique undertaking by utilizing land imaging and atmospheric satellites to build credible flood potential maps. At same time, we are also studying the potential occurrence and spread of Rift Valley Fever disease based on the short term climate records and precipitation data. These activities require multi-nation coordination and agreements and multiple operational agencies within each respective country. It also requires credible in situ data such as precipitation, river flow rates and lake levels to further validate the global and regional Hood models and algorithms. This also requires a considerable amount of training and capacity building for the RCMRD experts who will help us validate the model results and eventually transition it for operational use. In a final analysis, Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid Hood mapping and distribution, and e) validation of Hood forecasting and detection products.

Habib, Shahid↗
DOE OSTI2019

ZEUS Activation Foils Report for Experiments 1-5

The ZEUS experiments were conducted using the COMET vertical assembly machine at the Los Alamos Critical Experiments Facility (LACEF) at the Los Alamos National Laboratory (LANL). The experiments were designed to check the adequacy of cross sections in the intermediate-energy range. For the first four experiments, 12 kg highly enriched uranium (HEU) layers were sandwiched between different numbers of graphite plates in a vertical stack. In the first four experiments, a unit cell consisted of n graphite plates, an HEU layer, and then another n graphite plates. The unit cells were stacked until criticality was obtained. Experiments 1, 2, 3, and 4 contained decreasing amounts of graphite, where the unit cells value n was 4, 3, 2 and 1 respectively. In experiment 5 the HEU plates were in direct contact with each other to evaluate cross sections in the fast-energy range. A detailed description of experiments 1-4 is provided in reference, and of experiment 5, in reference. In order to investigate the cross sections in more detail, some ZEUS runs were made with activation foils inside the assemblies. Ratios of the activations of various foils are a standard method of measuring the gross neutron spectrum shape. A more detailed spectrum can be determined by simultaneously unfolding the response of several foils. This report describes the unfolding of the ZEUS activation foils data. The focus in this analysis is on the fast-energy range, especially at > 5 MeV.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1981

Solar magnetic structure and the solar activity cycle review of observational data

Data on solar magnetism that may offer clues for understanding stellar magnetism in general were reviewed. Magnetic phenomena in the photosphere and low chromosphere, where the magnetic structure can be studied in detail, are discussed. Properties of the discrete magnetic elements and their extensions through the chromosphere and transition zone up to the corona are described. The structure and evolution of active regions and other structured aggregates of magnetic elements are considered.

Zwaan, C.↗
DOE OSTI2014

Forward modeling transient brightenings and microflares around an active region observed with Hi-C

Small-scale flare-like brightenings around active regions are among the smallest and most fundamental of energetic transient events in the corona, providing a testbed for models of heating and active region dynamics. In a previous study, we modeled a large collection of these microflares observed with Hinode/X-Ray Telescope (XRT) using EBTEL and found that they required multiple heating events, but could not distinguish between multiple heating events on a single strand, or multiple strands each experiencing a single heating event. We present here a similar study, but with extreme-ultraviolet data of Active Region 11520 from the High Resolution Coronal Imager (Hi-C) sounding rocket. Hi-C provides an order of magnitude improvement to the spatial resolution of XRT, and a cooler temperature sensitivity, which combine to provide significant improvements to our ability to detect and model microflare activity around active regions. We have found that at the spatial resolution of Hi-C (≈0.''3), the events occur much more frequently than expected (57 events detected, only 1 or 2 expected), and are most likely made from strands of the order of 100 km wide, each of which is impulsively heated with multiple heating events. These findings tend to support bursty reconnection as the cause of the energy release responsible for the brightenings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Considerations for AMI-Based Operations for Distribution Feeders

More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Considerations for AMI-Based Operations for Distribution Feeders: Preprint

More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

Storm severity detection (RF)

Measurement of lightning location data which occur together with continental thunderstorms and hurricanes was examined, and a second phase linear interferometer was deployed. Electrical emission originating from tropical storms in the Gulf of Mexico were monitored. The time span between hurricane ALLEN (10 August 1980) and hurricane ALICIA (18 August 1983) represents the longest period that the United States has gone without hurricane landfall. Both systems were active and data were acquired during the landfall period of hurricane ALICIA.

Johnson, R. L.↗
DOE OSTI2015

Global carbon budget 2014

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO 2 emissions from fossil fuel combustion and cement production ( E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change ( E LUC ), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth ( G ATM ) is computed from the annual changes in concentration. The mean ocean CO 2 sink ( S OCEAN ) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S OCEAN is evaluated with data products based on surveys of ocean CO 2 measurements. The global residual terrestrial CO 2 sink ( S LAND ) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO 2 , and land-cover-change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ;, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004–2013), E FF was 8.9 ± 0.4 GtC yr⁻¹, E LUC 0.9 ± 0.5 GtC yr⁻¹, G ATM 4.3 ± 0.1 GtC yr⁻¹, S OCEAN 2.6 ± 0.5 GtC yr⁻¹, and S LAND 2.9 ± 0.8 GtC yr⁻¹. For year 2013 alone, E FF grew to 9.9 ± 0.5 GtC yr⁻¹, 2.3% above 2012, continuing the growth trend in these emissions, E LUC was 0.9 ± 0.5 GtC yr⁻¹, G ATM was 5.4 ± 0.2 GtC yr⁻¹, S OCEAN was 2.9 ± 0.5 GtC yr⁻¹, and S LAND was 2.5 ± 0.9 GtC yr⁻¹. G ATM was high in 2013, reflecting a steady increase in E FF and smaller and opposite changes between S OCEAN and S LAND compared to the past decade (2004–2013). The global atmospheric CO 2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that E FF will increase by 2.5% (1.3–3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO 2 yr⁻¹), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of E FF and assumed constant E LUC for 2014, cumulative emissions of CO 2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO 2 ) for 1870–2014, about 75% from E FF and 25% from E LUC . This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quéré et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center ( doi:10.3334/CDIAC/GCP_2014 ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Global Carbon Budget 2016

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO 2 emissions from fossil fuels and industry ( E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change ( E LUC ), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth ( G ATM ) is computed from the annual changes in concentration. The mean ocean CO 2 sink ( S OCEAN ) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S OCEAN is evaluated with data products based on surveys of ocean CO 2 measurements. The global residual terrestrial CO 2 sink ( S LAND ) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1 σ , reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), E FF was 9.3 ± 0.5 GtC yr -1 , E LUC 1.0 ± 0.5 GtC yr -1 , G ATM 4.5 ± 0.1 GtC yr -1 , S OCEAN 2.6 ± 0.5 GtC yr -1 , and S LAND 3.1 ± 0.9 GtC yr -1 . For year 2015 alone, the growth in E FF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr -1 , showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr -1 that took place during 2006–2015. Also, for 2015, E LUC was 1.3 ± 0.5 GtC yr -1 , G ATM was 6.3 ± 0.2 GtC yr -1 , S OCEAN was 3.0 ± 0.5 GtC yr -1 , and S LAND was 1.9 ± 0.9 GtC yr -1 . G ATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller S LAND for that year. The global atmospheric CO 2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in E FF with +0.2 % (range of -1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of E FF in 2016, the growth rate in atmospheric CO 2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink ( S LAND ) in response to El Niño conditions of 2015–2016. From this projection of E FF and assumed constant E LUC for 2016, cumulative emissions of CO 2 will reach 565 ± 55 GtC (2075 ± 205 GtCO 2 ) for 1870–2016, about 75 % from E FF and 25 % from E LUC . This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center ( doi:10.3334/CDIAC/GCP_2016 ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Global Carbon Budget 2015

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We also discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO 2 emissions from fossil fuels and industry ( E FF ) are based on energy statistics and cement production data, while emissions from land-use change ( E LUC ), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO 2 concentration is measured directly and its rate of growth ( G ATM ) is computed from the annual changes in concentration. Moreover, the mean ocean CO 2 sink ( S OCEAN ) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S OCEAN is evaluated with data products based on surveys of ocean CO 2 measurements. The global residual terrestrial CO 2 sink ( S LAND ) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO 2 , and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), E FF was 9.0 ± 0.5 GtC yr -1 , E LUC was 0.9 ± 0.5 GtC yr -1 , G ATM was 4.4 ± 0.1 GtC yr -1 , S OCEAN was 2.6 ± 0.5 GtC yr -1 , and S LAND was 3.0 ± 0.8 GtC yr -1 . For the year 2014 alone, E FF grew to 9.8 ± 0.5 GtC yr -1 , 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr -1 that took place during 2005–2014. Also, for 2014, E LUC was 1.1 ± 0.5 GtC yr -1 , G ATM was 3.9 ± 0.2 GtC yr -1 , S OCEAN was 2.9 ± 0.5 GtC yr -1 , and S LAND was 4.1 ± 0.9 GtC yr -1 . G ATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger S LAND for that year. The global atmospheric CO 2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in E FF will be near or slightly below zero, with a projection of -0.6 [range of -1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of E FF and assumed constant E LUC for 2015, cumulative emissions of CO 2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO 2 ) for 1870–2015, about 75 % from E FF and 25 % from E LUC . Finally, this living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center ( doi:10.3334/CDIAC/GCP_2015 ).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

The Global Geophysical Fluids Center of IERS (and its Special Bureau for Mantle)

The Global Geophysical Fluids Center (GGFC) was established by the International Earth Rotation Service (IERS) on IERS's 10th anniversary day January 1, 1998, in an effort to expand IERS's services to the scientific community. Under the GGFC, eight Special Bureaus (SB) have been selected, each to be responsible for research and data service activities pertaining to mass transports and related geophysical processes in specific components of the Earth system, or "global geophysical fluids," including the atmosphere, oceans, solid Earth, core, and geophysical processes of gravity, loading, tides and hydrological cycles. GGFC and the SBs have the responsibility of supporting, facilitating, and providing services to the worldwide research community, in areas related to the variations in Earth rotation, gravity field and geocenter that are caused by mass transport in the global geophysical fluids. These minute variations have been observed by various space geodetic techniques, as effective remote sensing tools, with ever increasing precision/accuracy and temporal/spatial resolution. The GGFC and SBs have organized dedicated workshops and special sessions at international conferences, published articles, and held regular business meetings. The SBs also maintain individual website for data services and information exchanges. See URL . In particular, the SB for Mantle focuses on large-scale mass redistributions that occur in the mantle in association with various dynamic processes, including seismic activities, the post-glacial rebound, and mantle convections.

Chao, Benjamin F.↗
NASA NTRS2018

Advances in Above- and In-Water Radiometry, Volume 3: Hybridspectral Next-Generation Optical Instruments

This publication documents the scientific advances associated with new instrument systems and accessories built to improve above- and in-water observations of the apparent optical properties (AOPs) for a diversity of water masses, including optically complex waters. The principal objective is to be prepared for the launch of next-generation ocean color satellites with the most capable commercial off-the-shelf (COTS) instrumentation in the shortest time possible. The technologies described herein are entirely new hybrid sampling capabilities, so as to satisfy the requirements established for next-generation missions. Both above- and in-water instruments are documented with software options for autonomous control of data collection activities as applicable. The instruments were developed for the Hybridspectral Alternative for Remote Profiling of Optical Observations for NASA Satellites (HARPOONS) vicarious calibration project. The state-of-the-art accuracy required for vicarious calibration also led to the development of laboratory instruments to ensure the field observations were within uncertainty requirements. Separate detailed presentations of the individual instruments provide the hardware designs, accompanying software for data acquisition and processing, and examples of the results achieved.

Hooker, Stanford B.↗