Simulations of carbon fluxes with terrestrial biosphere models still exhibit significant uncertainties, in part due to the uncertainty in model parameter values. With the advent of satellite ...measurements of solar induced chlorophyll fluorescence (SIF), there exists a novel pathway for constraining simulated carbon fluxes and parameter values. We investigate the utility of SIF in constraining gross primary productivity (GPP). As a first test we assess whether SIF simulations are sensitive to important parameters in a biosphere model. SIF measurements at the wavelength of 755 nm are simulated by the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. Idealized sensitivity tests of the SCOPE model stand-alone indicate strong sensitivity of GPP to the carboxylation capacity (Vcmax) and of SIF to the chlorophyll AB content (Cab) and incoming short wave radiation. Low sensitivity is found for SIF to Vcmax, however the relationship is subtle, with increased sensitivity under high radiation conditions and lower Vcmax ranges. CCDAS simulates well the patterns of satellite-measured SIF suggesting the combined model is capable of ingesting the data. CCDAS supports the idealized sensitivity tests of SCOPE, with SIF exhibiting sensitivity to Cab and incoming radiation, both of which are treated as perfectly known in previous CCDAS versions. These results demonstrate the need for careful consideration of Cab and incoming radiation when interpreting SIF and the limitations of utilizing SIF to constrain Vcmax in the present set-up in the CCDAS system.
We present far-infrared observations of Monoceros R2 (a giant molecular cloud at approximately 830 pc distance, containing several sites of active star formation), as observed at 70 μm, 160 μm, 250 ...μm, 350 μm, and 500 μm by the Photodetector Array Camera and Spectrometer (PACS) and Spectral and Photometric Imaging Receiver (SPIRE) instruments on the Herschel Space Observatory as part of the Herschel imaging survey of OB young stellar objects (HOBYS) Key programme. The Herschel data are complemented by SCUBA-2 data in the submillimetre range, and WISE and Spitzer data in the mid-infrared. In addition, C18O data from the IRAM 30-m Telescope are presented, and used for kinematic information. Sources were extracted from the maps with getsources, and from the fluxes measured, spectral energy distributions were constructed, allowing measurements of source mass and dust temperature. Of177 Herschel sources robustly detected in the region (a detection with high signal-to-noise and low axis ratio at multiple wavelengths), including protostars and starless cores, 29 are found in a filamentary hub at the centre of the region (a little over 1% of the observed area). These objects are on average smaller, more massive, and more luminous than those in the surrounding regions (which together suggest that they are at a later stage of evolution), a result that cannot be explained entirely by selection effects. These results suggest a picture in which the hub may have begun star formation at a point significantly earlier than the outer regions, possibly forming as a result of feedback from earlier star formation. Furthermore, the hub may be sustaining its star formation by accreting material from the surrounding filaments.
Atmospheric CO2 inversions estimate surface carbon fluxes from an optimal fit to atmospheric CO2 measurements, usually including prior constraints on the flux estimates. Eleven sets of carbon flux ...estimates are compared, generated by different inversions systems that vary in their inversions methods, choice of atmospheric data, transport model and prior information. The inversions were run for at least 5 yr in the period between 1990 and 2010. Mean fluxes for 2001-2004, seasonal cycles, interannual variability and trends are compared for the tropics and northern and southern extra-tropics, and separately for land and ocean. Some continental/basin-scale subdivisions are also considered where the atmospheric network is denser. Four-year mean fluxes are reasonably consistent across inversions at global/latitudinal scale, with a large total (land plus ocean) carbon uptake in the north (-3.4 Pg C yr-1 (±0.5 Pg C yr-1 standard deviation), with slightly more uptake over land than over ocean), a significant although more variable source over the tropics (1.6 ± 0.9 Pg C yr-1 ) and a compensatory sink of similar magnitude in the south (-1.4 ± 0.5 Pg C yr-1 ) corresponding mainly to an ocean sink. Largest differences across inversions occur in the balance between tropical land sources and southern land sinks. Interannual variability (IAV) in carbon fluxes is larger for land than ocean regions (standard deviation around 1.06 versus 0.33 Pg C yr-1 for the 1996-2007 period), with much higher consistency among the inversions for the land. While the tropical land explains most of the IAV (standard deviation ~ 0.65 Pg C yr-1 ), the northern and southern land also contribute (standard deviation ~ 0.39 Pg C yr-1 ). Most inversions tend to indicate an increase of the northern land carbon uptake from late 1990s to 2008 (around 0.1 Pg C yr-1 , predominantly in North Asia. The mean seasonal cycle appears to be well constrained by the atmospheric data over the northern land (at the continental scale), but still highly dependent on the prior flux seasonality over the ocean. Finally we provide recommendations to interpret the regional fluxes, along with the uncertainty estimates.
We present a new version of the Met Office Hadley Centre/Climatic Research Unit global surface temperature data set, HadCRUT5. HadCRUT5 presents monthly average near‐surface temperature anomalies, ...relative to the 1961–1990 period, on a regular 5° latitude by 5° longitude grid from 1850 to 2018. HadCRUT5 is a combination of sea‐surface temperature (SST) measurements over the ocean from ships and buoys and near‐surface air temperature measurements from weather stations over the land surface. These data have been sourced from updated compilations and the adjustments applied to mitigate the impact of changes in SST measurement methods have been revised. Two variants of HadCRUT5 have been produced for use in different applications. The first represents temperature anomaly data on a grid for locations where measurement data are available. The second, more spatially complete, variant uses a Gaussian process based statistical method to make better use of the available observations, extending temperature anomaly estimates into regions for which the underlying measurements are informative. Each is provided as a 200‐member ensemble accompanied by additional uncertainty information. The combination of revised input data sets and statistical analysis results in greater warming of the global average over the course of the whole record. In recent years, increased warming results from an improved representation of Arctic warming and a better understanding of evolving biases in SST measurements from ships. These updates result in greater consistency with other independent global surface temperature data sets, despite their different approaches to data set construction, and further increase confidence in our understanding of changes seen.
Plain Language Summary
We have produced a new version of a data set that measures changes of near‐surface temperature across the globe from 1850 to 2018, called HadCRUT5. We have included an improved data set of sea‐surface temperature, which better accounts for the effects of changes through time in how measurement were made from ships and buoys at sea. We have also included an expanded compilation of measurements made at weather stations on land. There are two variations of HadCRUT5, produced for different uses. The first, the “HadCRUT5 noninfilled data set,” maps temperature changes on a grid for locations close to where we have measurements. The second, the “HadCRUT5 analysis,” extends our estimates to locations further from the available measurements using a statistical technique that makes use of the spatial connectedness of temperature patterns. This improves the representation of less well observed regions in estimates of global, hemispheric and regional temperature change. Together, these updates and improvements reveal a slightly greater rise in near‐surface temperature since the nineteenth century, especially in the Northern Hemisphere, which is more consistent with other data sets. This increases our confidence in our understanding of global surface temperature changes since the mid‐19th century.
Key Points
We have created a new version of the Met Office Hadley Centre and Climatic Research Unit global surface temperature data set for 1850–2018
The new data set better represents sparsely observed regions of the globe and incorporates an improved sea‐surface temperature data set
This data set shows increased global average warming since the mid‐19th century and in recent years, consistent with other analyses
Systematic, operational, long‐term observations of the terrestrial carbon cycle (including its interactions with water, energy and nutrient cycles and ecosystem dynamics) are important for the ...prediction and management of climate, water resources, food resources, biodiversity and desertification. To contribute to these goals, a terrestrial carbon observing system requires the synthesis of several kinds of observation into terrestrial biosphere models encompassing the coupled cycles of carbon, water, energy and nutrients. Relevant observations include atmospheric composition (concentrations of CO2 and other gases); remote sensing; flux and process measurements from intensive study sites; in situ vegetation and soil monitoring; weather, climate and hydrological data; and contemporary and historical data on land use, land use change and disturbance (grazing, harvest, clearing, fire).
A review of model–data synthesis tools for terrestrial carbon observation identifies ‘nonsequential’ and ‘sequential’ approaches as major categories, differing according to whether data are treated all at once or sequentially. The structure underlying both approaches is reviewed, highlighting several basic commonalities in formalism and data requirements.
An essential commonality is that for all model–data synthesis problems, both nonsequential and sequential, data uncertainties are as important as data values themselves and have a comparable role in determining the outcome.
Given the importance of data uncertainties, there is an urgent need for soundly based uncertainty characterizations for the main kinds of data used in terrestrial carbon observation. The first requirement is a specification of the main properties of the error covariance matrix.
As a step towards this goal, semi‐quantitative estimates are made of the main properties of the error covariance matrix for four kinds of data essential for terrestrial carbon observation: remote sensing of land surface properties, atmospheric composition measurements, direct flux measurements, and measurements of carbon stores.
This paper presents the space‐time distribution of terrestrial carbon fluxes for the period 1979–1999 generated by a terrestrial carbon cycle data assimilation system (CCDAS). CCDAS is based around ...the Biosphere Energy Transfer Hydrology model. We assimilate satellite observations of photosynthetically active radiation and atmospheric CO2 concentration observations in a two‐step process. The control variables for the assimilation are the parameters of the carbon cycle model. The optimized model produces a moderate fit to the seasonal cycle of atmospheric CO2 concentration and a good fit to its interannual variability. Long‐term mean fluxes show large uptakes over the northern midlatitudes and uptakes over tropical continents partly offsetting the prescribed efflux due to land use change. Interannual variability is dominated by the tropics. On interannual timescales the controlling process is net primary productivity (NPP) while for decadal changes the main driver is changes in soil respiration. An adjoint sensitivity analysis reveals that uncertainty in long‐term storage efficiency of soil carbon is the largest contributor to uncertainty in net flux.
Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800 000 years. Those elevated GHG concentrations warm the planet and – partially offset ...by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3 ppm, CH4 at 808.2 ppb and N2O at 273.0 ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).
High‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data ...assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.
Key Points
Gridded high‐resolution time series of global fossil fuel CO2 emissions is generatedIn situ remote sensing data integrated into fossil fuel data assimilation systemSpatial patterns of recession are analyzed using CO2 emissions time series
T2K reports its first results in the search for CP violation in neutrino oscillations using appearance and disappearance channels for neutrino- and antineutrino-mode beams. The data include all runs ...from January 2010 to May 2016 and comprise 7.482×10^{20} protons on target in neutrino mode, which yielded in the far detector 32 e-like and 135 μ-like events, and 7.471×10^{20} protons on target in antineutrino mode, which yielded 4 e-like and 66 μ-like events. Reactor measurements of sin^{2}2θ_{13} have been used as an additional constraint. The one-dimensional confidence interval at 90% for the phase δ_{CP} spans the range (-3.13, -0.39) for normal mass ordering. The CP conservation hypothesis (δ_{CP}=0, π) is excluded at 90% C.L.
Aims. To constrain models of high-mass star formation, the Herschel-HOBYS key program aims at discovering massive dense cores (MDCs) able to host the high-mass analogs of low-mass prestellar cores, ...which have been searched for over the past decade. We here focus on NGC 6334, one of the best-studied HOBYS molecular cloud complexes. Methods. We used Herschel/PACS and SPIRE 70−500 μm images of the NGC 6334 complex complemented with (sub)millimeter and mid-infrared data. We built a complete procedure to extract ~0.1 pc dense cores with the getsources software, which simultaneously measures their far-infrared to millimeter fluxes. We carefully estimated the temperatures and masses of these dense cores from their spectral energy distributions (SEDs). We also identified the densest pc-scale cloud structures of NGC 6334, one 2 pc × 1 pc ridge and two 0.8 pc × 0.8 pc hubs, with volume-averaged densities of ~105 cm-3. Results. A cross-correlation with high-mass star formation signposts suggests a mass threshold of 75 M⊙ for MDCs in NGC 6334. MDCs have temperatures of 9.5−40 K, masses of 75−1000 M⊙, and densities of 1 × 105−7 × 107 cm-3. Their mid-infrared emission is used to separate 6 IR-bright and 10 IR-quiet protostellar MDCs while their 70 μm emission strength, with respect to fitted SEDs, helps identify 16 starless MDC candidates. The ability of the latter to host high-mass prestellar cores is investigated here and remains questionable. An increase in mass and density from the starless to the IR-quiet and IR-bright phases suggests that the protostars and MDCs simultaneously grow in mass. The statistical lifetimes of the high-mass prestellar and protostellar core phases, estimated to be 1−7 × 104 yr and at most 3 × 105 yr respectively, suggest a dynamical scenario of high-mass star formation. Conclusions. The present study provides good mass estimates for a statistically significant sample, covering the earliest phases of high-mass star formation. High-mass prestellar cores may not exist in NGC 6334, favoring a scenario presented here, which simultaneously forms clouds, ridges, MDCs, and high-mass protostars.
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