171 research outputs found

    Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO2 and water fluxes through combined in situ measurements and ecosystem modelling

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    Water stress is a defining characteristic of Mediterranean ecosystems, and is likely to become more severe in the coming decades. Simulation models are key tools for making predictions, but our current understanding of how soil moisture controls ecosystem functioning is not sufficient to adequately constrain parameterisations. Canopy-scale flux data from four forest ecosystems with Mediterranean-type climates were used in order to analyse the physiological controls on carbon and water flues through the year. Significant non-stomatal limitations on photosynthesis were detected, along with lesser changes in the conductance-assimilation relationship. New model parameterisations were derived and implemented in two contrasting modelling approaches. The effectiveness of two models, one a dynamic global vegetation model ('ORCHIDEE'), and the other a forest growth model particularly developed for Mediterranean simulations ('GOTILWA+'), was assessed and modelled canopy responses to seasonal changes in soil moisture were analysed in comparison with in situ flux measurements. In contrast to commonly held assumptions, we find that changing the ratio of conductance to assimilation under natural, seasonally-developing, soil moisture stress is not sufficient to reproduce forest canopy CO2 and water fluxes. However, accurate predictions of both CO2 and water fluxes under all soil moisture levels encountered in the field are obtained if photosynthetic capacity is assumed to vary with soil moisture. This new parameterisation has important consequences for simulated responses of carbon and water fluxes to seasonal soil moisture stress, and should greatly improve our ability to anticipate future impacts of climate changes on the functioning of ecosystems in Mediterranean-type climates

    Decomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISI-MIP results

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    We examined the changes to global net primary production (NPP), vegetation biomass carbon (VegC), and soil organic carbon (SOC) estimated by six global vegetation models (GVMs) obtained from the Inter-Sectoral Impact Model Intercomparison Project. Simulation results were obtained using five global climate models (GCMs) forced with four representative concentration pathway (RCP) scenarios. To clarify which component (i.e., emission scenarios, climate projections, or global vegetation models) contributes the most to uncertainties in projected global terrestrial C cycling by 2100, analysis of variance (ANOVA) and wavelet clustering were applied to 70 projected simulation sets. At the end of the simulation period, changes from the year 2000 in all three variables varied considerably from net negative to positive values. ANOVA revealed that the main sources of uncertainty are different among variables and depend on the projection period. We determined that in the global VegC and SOC projections, GVMs are the main influence on uncertainties (60 % and 90 %, respectively) rather than climate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes in vegetation carbon residence times is dominated by GVM uncertainty, particularly in the latter half of the 21st century. In addition, we found that the contribution of each uncertainty source is spatiotemporally heterogeneous and it differs among the GVM variables. The dominant uncertainty source for changes in NPP and VegC varies along the climatic gradient. The contribution of GVM to the uncertainty decreases as the climate division becomes cooler (from ca. 80 % in the equatorial division to 40 % in the snow division). Our results suggest that to assess climate change impacts on global ecosystem C cycling among each RCP scenario, the long-term C dynamics within the ecosystems (i.e., vegetation turnover and soil decomposition) are more critical factors than photosynthetic processes. The different trends in the contribution of uncertainty sources in each variable among climate divisions indicate that improvement of GVMs based on climate division or biome type will be effective. On the other hand, in dry regions, GCMs are the dominant uncertainty source in climate impact assessments of vegetation and soil C dynamics

    A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

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    Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

    Measurement of ΜˉΌ\bar{\nu}_{\mu} and ΜΌ\nu_{\mu} charged current inclusive cross sections and their ratio with the T2K off-axis near detector

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    We report a measurement of cross section σ(ΜΌ+nucleus→Ό−+X)\sigma(\nu_{\mu}+{\rm nucleus}\rightarrow\mu^{-}+X) and the first measurements of the cross section σ(ΜˉΌ+nucleus→Ό++X)\sigma(\bar{\nu}_{\mu}+{\rm nucleus}\rightarrow\mu^{+}+X) and their ratio R(σ(Μˉ)σ(Îœ))R(\frac{\sigma(\bar \nu)}{\sigma(\nu)}) at (anti-)neutrino energies below 1.5 GeV. We determine the single momentum bin cross section measurements, averaged over the T2K Μˉ/Îœ\bar{\nu}/\nu-flux, for the detector target material (mainly Carbon, Oxygen, Hydrogen and Copper) with phase space restricted laboratory frame kinematics of ΞΌ\theta_{\mu}500 MeV/c. The results are σ(Μˉ)=(0.900±0.029(stat.)±0.088(syst.))×10−39\sigma(\bar{\nu})=\left( 0.900\pm0.029{\rm (stat.)}\pm0.088{\rm (syst.)}\right)\times10^{-39} and $\sigma(\nu)=\left( 2.41\ \pm0.022{\rm{(stat.)}}\pm0.231{\rm (syst.)}\ \right)\times10^{-39}inunitsofcm in units of cm^{2}/nucleonand/nucleon and R\left(\frac{\sigma(\bar{\nu})}{\sigma(\nu)}\right)= 0.373\pm0.012{\rm (stat.)}\pm0.015{\rm (syst.)}$.Comment: 18 pages, 8 figure

    Methane and carbon dioxide fluxes and their regional scalability for the European Arctic wetlands during the MAMM project in summer 2012

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    Airborne and ground-based measurements of methane (CH4), carbon dioxide (CO2) and boundary layer thermodynamics were recorded over the Fennoscandian landscape (67–69.5° N, 20–28° E) in July 2012 as part of the MAMM (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling) field campaign. Employing these airborne measurements and a simple boundary layer box model, net regional-scale (~ 100 km) fluxes were calculated to be 1.2 ± 0.5 mg CH4 h−1 m−2 and −350 ± 143 mg CO2 h−1 m−2. These airborne fluxes were found to be relatively consistent with seasonally averaged surface chamber (1.3 ± 1.0 mg CH4 h−1 m−2) and eddy covariance (1.3 ± 0.3 mg CH4 h−1 m−2 and −309 ± 306 mg CO2 h−1 m−2) flux measurements in the local area. The internal consistency of the aircraft-derived fluxes across a wide swath of Fennoscandia coupled with an excellent statistical comparison with local seasonally averaged ground-based measurements demonstrates the potential scalability of such localised measurements to regional-scale representativeness. Comparisons were also made to longer-term regional CH4 climatologies from the JULES (Joint UK Land Environment Simulator) and HYBRID8 land surface models within the area of the MAMM campaign. The average hourly emission flux output for the summer period (July–August) for the year 2012 was 0.084 mg CH4 h−1 m−2 (minimum 0.0 and maximum 0.21 mg CH4 h−1 m−2) for the JULES model and 0.088 mg CH4 h−1 m−2 (minimum 0.0008 and maximum 1.53 mg CH4 h−1 m−2) for HYBRID8. Based on these observations both models were found to significantly underestimate the CH4 emission flux in this region, which was linked to the under-prediction of the wetland extents generated by the models

    Search for astrophysical electron antineutrinos in Super-Kamiokande with 0.01wt% gadolinium-loaded water

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    We report the first search result for the flux of astrophysical electron antineutrinos for energies O(10) MeV in the gadolinium-loaded Super-Kamiokande (SK) detector. In June 2020, gadolinium was introduced to the ultra-pure water of the SK detector in order to detect neutrons more efficiently. In this new experimental phase, SK-Gd, we can search for electron antineutrinos via inverse beta decay with efficient background rejection and higher signal efficiency thanks to the high efficiency of the neutron tagging technique. In this paper, we report the result for the initial stage of SK-Gd with a 22.5×55222.5\times552 kton⋅day\rm kton\cdot day exposure at 0.01% Gd mass concentration. No significant excess over the expected background in the observed events is found for the neutrino energies below 31.3 MeV. Thus, the flux upper limits are placed at the 90% confidence level. The limits and sensitivities are already comparable with the previous SK result with pure-water (22.5×2970kton⋅day22.5 \times 2970 \rm kton\cdot day) owing to the enhanced neutron tagging

    Search for Lorentz and CPT violation using sidereal time dependence of neutrino flavor transitions over a short baseline

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    A class of extensions of the Standard Model allows Lorentz and CPT violations, which can be identified by the observation of sidereal modulations in the neutrino interaction rate. A search for such modulations was performed using the T2K on-axis near detector. Two complementary methods were used in this study, both of which resulted in no evidence of a signal. Limits on associated Lorentz and CPT-violating terms from the Standard Model extension have been derived by taking into account their correlations in this model for the first time. These results imply such symmetry violations are suppressed by a factor of more than 10 20 at the GeV scale
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