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Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90° N) and younger tropical (23° S–23° N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50° N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C/sq. myr but as high as 0.60 kg C/sq. myr where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.
This research is based on the exploration of tectonic patterns on Titan from a global perspective. Several moons in the outer solar system display patterns of surface tectonic features that imply global stress fields driven or modified by global forces. Patterns such as these are seen in Europa's tidally induced fracture patterns, Enceladus's tiger stripes, and Ganymede's global expansion induced normal fault bands. Given its proximity to Saturn, as well as its eccentric orbit, tectonic features and global stresses may be present on Titan as well. Titan displays possible tectonic structures, such as mountain chains along its equator (Radebaugh et al. 2007), as well as the unexplored dark linear streaks termed virgae by the IAU. Imaged by Cassini with the RADAR instrument, mountain chains near the equator are observed with a predominante east-west orientation (Liu et al. 2012, Mitri et al. 2010). Orientations such as these can be explained by modifications in the global tidal stress field induced by global contraction followed by rotational spin-up. Also, due to Titan's eccentric orbit, its current rotation rate may be in an equilibrium between tidal spin-up near periapsis and spin-down near apoapsis (Barnes and Fortney 2003). Additional stress from rotational spin-up provides an asymmetry to the stress field. This, combined with an isotropic stress from radial contraction, favors the formation of equatorial mountain chains in an east-west direction. The virgae, which have been imaged by Cassini with both the Visual and Infrared Mapping Spectrometer (VIMS) and Imaging Science Subsystem (ISS) instruments, are located predominately near 30 degrees latitude in either hemisphere. Oriented with a pronounced elongation in the east-west direction, all observed virgae display similar characteristics: similar relative albedos as the surrounding terrain however darkened with an apparent neutral absorber, broken-linear or rounded sharp edges, and connected, angular elements with distinct, linear edges. Virgae imaged during northern latitude passes are oriented with their long dimensions toward Titan's antiSaturn point. If the virgae are of tectonic origin, for instance if the turn out to be i.e. grabens, they could serve as markers to Titan's global stress field. Using them in this way allows for a mapping of global tectonic patterns. These patterns will be tested for consistency against the various sources of global stress and orientations of mountain chains. By determining what drives Titan's tectonics globally, we will be able to place Titan within the context of the other outer planet icy satellites.
The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P < 0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and a CDOC (r =0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250-800 nm. These unassimilated radiances were within 0.074 mW/sq cm/micron/sr of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of 10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PACE, ocean color, water-leaving radiances, biogeochemical model, radiative transfer model
The major components of the global fresh water cycle include the evaporation from the land and ocean surfaces, precipitation onto the Ocean and land surfaces, the net atmospheric transport of water from oceanic areas over land, and the return flow of water from the land back into the ocean. The additional components of oceanic water transport are few, principally, the mixing of fresh water through the oceanic boundary layer, transport by ocean currents, and sea ice processes. On land the situation is considerably more complex, and includes the deposition of rain and snow on land; water flow in runoff; infiltration of water into the soil and groundwater; storage of water in soil, lakes and streams, and groundwater; polar and glacial ice; and use of water in vegetation and human activities. Knowledge of the key terms in the fresh water flux budget is poor. Some components of the budget, e.g. precipitation, runoff, storage, are measured with variable accuracy across the globe. We are just now obtaining precise measurements of the major components of global fresh water storage in global ice and ground water. The easily accessible fresh water sources in rivers, lakes and snow runoff are only adequately measured in the more affluent portions of the world. presents proposals are suggesting methods of making global measurements of these quantities from space. At the same time, knowledge of the global fresh water resources under the effects of climate change is of increasing importance and the human population grows. This paper provides an overview of the state of knowledge of the global fresh water budget, evaluating the accuracy of various global water budget measuring and modeling techniques. We review the measurement capabilities of satellite instruments as compared with field validation studies and modeling approaches. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest priorities for future improvements in global fresh water budget monitoring. The priorities are based on the potential of new approaches to provide improved measurement and modeling systems, and on the need to measure and understand the potential for a speed-up of the global water cycle under the effects of climate change.
Many hydrological models have been introduced in the hydrological literature to predict runoff but few of these have become common planning or decision-making tools, either because the data requirements are substantial or because the modeling processes are too complicated for operational application. On the other hand, progress in regional or global rainfall-runoff simulation has been constrained by the difficulty of measuring spatiotemporal variability of the primary causative factor, i.e. rainfall fluxes, continuously over space and time. Building on progress in remote sensing technology, researchers have improved the accuracy, coverage, and resolution of rainfall estimates by combining imagery from infrared, passive microwave, and space-borne radar sensors. Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports a ballpark assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conservation Service (NRCS) runoff Curve Number (CN) method. Using an Antecedent Precipitation Index (API) as a proxy of antecedent moisture conditions, this note estimates time-varying NRCS-CN values determined by the 5-day normalized API. Driven by multi-year (1998-2006) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis, quasi-global runoff was retrospectively simulated with the NRCS-CN method and compared to Global Runoff Data Centre data at global and catchment scales. Results demonstrated the potential for using this simple method when diagnosing runoff values from satellite rainfall for the globe and for medium to large river basins. This work was done with the simple NRCS-CN method as a first-cut approach to understanding the challenges that lie ahead in advancing the satellite-based inference of global runoff. We expect that the successes and limitations revealed in this study will lay the basis for applying more advanced methods to capture the dynamic variability of the global hydrologic process for global runoff monlto~ngin real time. The essential ingredient in this work is the use of global satellite-based rainfall estimation.
The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (approximately biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modeling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations).For the 2003-2012 decade, global methane emissions are estimated by top-down inversions at 558 TgCH4 yr(exp -1), range 540-568. About 60 of global emissions are anthropogenic (range 50-65%). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 TgCH4 yr(exp -1), range 596-884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (approximately 64% of the global budget, less than 30deg N) as compared to mid (approximately 32%, 30-60deg N) and high northern latitudes (approximately 4%, 60-90deg N). Top-down inversions consistently infer lower emissions in China (approximately 58 TgCH4 yr(exp -1), range 51-72, minus14% ) and higher emissions in Africa (86 TgCH4 yr(exp -1), range 73-108, plus 19% ) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_ METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.
Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.
The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.
As a result of developments occurring over the last two decades, the data acquisition, storage, analysis, and transmission facilities are now available for a concerted long-term interdisciplinary and international study of the global environmental system. Such a study is the essence of the 'Global Habitability' concept introduced in 1982. The aims of Global Habitability research are considered, taking into account an understanding of the vital global processes of the earth's energy balance, the global hydrological cycle, and the biogeochemical cycling of carbon, nitrogen, phosphorus, and sulfur. Details of NASA planning for Global Habitability are discussed along with international data exchange arrangements. Attention is given to the possible contributions of satellite data and associated techniques to Global Habitability, examples of specific research conducted by NASA in support of the Global Habitability and the international sharing of data and results for Global Habitability.
Although clouds are produced by "micro-scale" processes, these processes operate as a response to global-scale atmospheric motions to produce the complex geographic distribution of clouds on Earth. One way to attack this larger-scale problem is to combine global-scale satellite observations of cloud property variations with global-scale determinations of the atmospheric circulation. Such a global data analysis can be used to describe the mean characteristics of clouds and their variations for comparison with global circulation models, to identify systematic relations among observed cloud properties and atmospheric motions, or to estimate, directly, the derivative relations of the processes at work using statistical life-cycle-composites of cloud system evolution. Another approach is to find what characteristics of the global atmospheric circulation are revealed in observed global-scale cloud variations. For the first time this type of analysis is possible with the advent of global, satellite-based cloud (ISCCP), precipitation (microwave-based), and water vapor (merged infrared and microwave) datasets, together with global wind datasets (ECMWF and NCEP re-analyses), all of which resolve features at least down to the upper end of the mesoscale and cover more than a decade. We report on some preliminary attempts to identify quantitative relationships between atmospheric motions and cloud properties that are relevant to cloud processes. Three examples are given: (1) cloud variations at the smallest scales and what they reveal about the nature of small-scale turbulence in the atmospheric boundary layer, (2) cloud variations at "moderate" weather-scales and what they reveal about meteorological storm systems, and (3) cloud variations at the largest scales and what they indicate about interannual variations of climate.
The surface turbulent fluxes of momentum, latent heat, and sensible heat over global oceans are essential to weather, climate and ocean problems. Evaporation is a key component of the hydrological cycle and the surface heat budget, while the wind stress is the major forcing for driving the oceanic circulation. The global air-sea fluxes of momentum, latent and sensible heat, radiation, and freshwater (precipitation-evaporation) are the forcing for driving oceanic circulation and, hence, are essential for understanding the general circulation of global oceans. The global air-sea fluxes are required for driving ocean models and validating coupled ocean-atmosphere global models. We have produced a 7.5-year (July 1987-December 1994) dataset of daily surface turbulent fluxes over the global oceans from the Special Sensor microwave/Imager (SSM/I) data. Daily turbulent fluxes were derived from daily data of SSM/I surface winds and specific humidity, National Centers for Environmental Prediction (NCEP) sea surface temperatures, and European Centre for Medium-Range Weather Forecasts (ECMWF) air-sea temperature differences, using a stability-dependent bulk scheme. The retrieved instantaneous surface air humidity (with a 25-km resolution) validated well with that of the collocated radiosonde observations over the global oceans. Furthermore, the retrieved daily wind stresses and latent heat fluxes were found to agree well with that of the in situ measurements (IMET buoy, RV Moana Wave, and RV Wecoma) in the western Pacific warm pool during the TOGA COARE intensive observing period (November 1992-February 1993). The global distributions of 1988-94 seasonal-mean turbulent fluxes will be presented. In addition, the global distributions of 1990-93 annual-means turbulent fluxes and input variables will be compared with those of UWM/COADS covering the same period. The latter is based on the COADS (comprehensive ocean-atmosphere data set) and is recognized to be one of the best climatological analyses of fluxes derived from ship observations.
Conventional magnetograms and chromospheric and coronal images show qualitatively that the fastest coronal mass ejections (CMEs) are magnetic explosions from sunspot active regions where the magnetic field is globally strongly sheared and twisted from its minimum-energy potential configuration. We present measurements from active region vector magnetograms that start to quantify the dependence of an active region's CME productivity on the global nonpotentiality of its magnetic field. From each of 17 magnetograms of 12 bipolar active regions, we measured the size of the active region (the magnetic flux content, phi) and three separate measures of the global nonpotentiality (L(sub SS), the length of strong-shear, strong-field main neutral line: I(sub N), the net electric current connecting one polarity to the other; and alpha = (mu)I(sub N)/phi), a flux normalized measure of the field twist). From these measurements and the observed CME productivity of the active regions, we find that: (1) All three measures of global nonpotentiality are statistically correlated with the active region flux content and with each other; (2) All three measures of global nonpotentiality are significantly correlated with CME productivity. The flux content correlates with CME productivity, but at a lower statistically significant confidence level (less than 95%); (3) The net current is less closely correlated with CME productivity than alpha and the correlation of CME productivity with flux content is even weaker. If these differences in correlation strength, and a significant correlation of alpha with flux content, persist to larger active regions, this would imply that the size of active regions does not affect CME productivity except through global nonpotentiality; and (4) For each of the four global magnetic quantities, the correlation with CME productivity is stronger for a two-day time window for the CME production than for windows half as wide or twice as wide. This plausibly is a result of the most counterproductive active regions producing less than one CME per day, and from the active region's evolution often significantly changing the global nonpotentiality over the course of several days. These results establish that measures of active region global nonpotentiality from vector magnetograms (such as L(sub SS), I(sub N), and alpha) should be useful for prediction a active region CMEs.
Scientific need and technological opportunity require that we move toward implementing a global network of geodetic fiducial stations which feature co-located SLR, VLBI, GNSS, and DORIS instrumentation. Earth science of the next decade will require more accurate global change measurements of sea level topography, sea level change, polar ice mass balance, hydrological and atmospheric mass flux. and topographic deformation, real time mm scale navigation and precision time transfer on a global scale. These scientific requirements have been translated into a goal of mm scale annual stability for the terrestrial reference frame, earth orientation parameters, as well as the orbit and clock determinations tbr the GNSS systems. To meet these challenges, the four geodetic observing systems must be more tightly integrated in technology, location, and analysis. NASA strongly supports the objectives of the IGGOS initiative vis NASA's National Geodetic Observatory and INDIGO programs. The Global networks of GNSS, SLR. and VLBI observatories are for the most part poorly suited for these new demands. These important geodetic networks have evolved with little planning yet these systems are providing essential measurements to a wide swath of society. New signal structures in the GPS and the developing Galileo GNSS will soon require replacement of the GNSS receivers. The SLR network is poorly distributed globally, requires labor intensive observations and analysis, and for the most part relies upon antiquated technology. The VLBI observatories utilize large radio telescopes in remote regions that are poorly distributed globally. Co-location of these networks is sparse and co-location errors contribute significantly to the observing error spectrum. Increasing use of the S and X band by commercial and other government services will also contribute to increased observational errors. The time is upon us for an international effort to develop an optimized global geodetic fiducial network of twelve or more integrated automated geodetic observatories that will provide in near real time high density mea.surements of Earth orientation, geodetic positioning, and GNSS system monitoring. The strategic goal for the optimized global fiducial network should be efficient autonomous operation, real time data streaming to analysis centers with an integrated near real time analysis capability for all four observing systems. These goals are achievable in the next decade given the dramatic technological improvements in all geodetic systems. For VLBI, the BKG TIGO might be viewed as a preliminary prototype of technology for fundamental stations. Mark 5, PC-VSI. e-VLBI broadband development efforts are laying the groundwork to reduce the aperture of the VLBI antennas and to allow for precision mm level co-location of observing systems. Operating costs and enhanced accuracy would accrue from the elimination of hydrogen maser clocks using double differencing, GNSS time transfer technology, GHz broadband recording, real time analysis, and mm wavelength VLBI observations. A global geodetic fiducial network will not be realizable without international efforts and the support of the four services.
The U.S. Global Change Research Program (http://globalchange.gov) coordinates and integrates federal research on changes in the global environment and their implications for society. The USGCRP is developing a Global Change Information System (GCIS) that will centralize access to data and information related to global change across the U.S. federal government. The first implementation will focus on the 2013 National Climate Assessment (NCA) . (http://assessment.globalchange.gov) The NCA integrates, evaluates, and interprets the findings of the USGCRP; analyzes the effects of global change on the natural environment, agriculture, energy production and use, land and water resources, transportation, human health and welfare, human social systems, and biological diversity; and analyzes current trends in global change, both human-induced and natural, and projects major trends for the subsequent 25 to 100 years. The NCA has received over 500 distinct technical inputs to the process, many of which are reports distilling and synthesizing even more information, coming from thousands of individuals around the federal, state and local governments, academic institutions and non-governmental organizations. The GCIS will present a web-based version of the NCA including annotations linking the findings and content of the NCA with the scientific research, datasets, models, observations, etc. that led to its conclusions. It will use semantic tagging and a linked data approach, assigning globally unique, persistent, resolvable identifiers to all of the related entities and capturing and presenting the relationships between them, both internally and referencing out to other linked data sources and back to agency data centers. The developing W3C PROV Data Model and ontology will be used to capture the provenance trail and present it in both human readable web pages and machine readable formats such as RDF and SPARQL. This will improve visibility into the assessment process, increase understanding and reproducibility, and ultimately increase credibility and trust of the resulting report. Building on the foundation of the NCA, longer term plans for the GCIS include extending these capabilities throughout the U.S. Global Change Research Program, centralizing access to global change data and information across the thirteen agencies that comprise the program.
The maximum photosynthetic carboxylation rate (V (sub cmax)) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V(sub cmax) distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 petagrams of Carbon (PgC) per year, 65 percent of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27percent coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r equals 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V(sub cmax) variation in the field, particularly in northern latitudes.
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.