412 research outputs found

    Stable water isotopes in HadCM3: isotopic signature of El Nino-Southern Oscillation and the tropical amount effect

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    Stable water isotopes have been added to the full hydrological cycle of the Hadley Centre Climate model (HadCM3) coupled atmosphere-ocean GCM. Simulations of delta O-18 in precipitation and at the ocean surface compare well with observations for the present-day climate. The model has been used to investigate the isotopic anomalies associated with ENSO; it is found that the anomalous delta O-18 in precipitation is correlated with the anomalous precipitation amount in accordance with the "amount effect.'' The El Nino delta O-18 anomaly at the ocean surface is largest in coastal regions because of the mixing of ocean water and the more depleted runoff from the land surface. Coral delta O-18 anomalies were estimated, using an established empirical relationship, and generally reflect ocean surface delta O-18 anomalies in coastal regions and sea surface temperatures away from the coast. The spatial relationship between tropical precipitation and delta O-18 was investigated for the El Nino anomaly simulated by HadCM3. Weighting the El Nino precipitation anomaly by the precipitation amount at each grid box gave a large increase in the spatial correlation between tropical precipitation and delta O-18. This improvement was most apparent over land points and between 10 and 20 degrees of latitude

    Transient simulations of the last 22,000 years, with a fully dynamic atmosphere in the GENIE earth-system framework

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    This paper presents and discusses an ensemble of transient model simulations from the Last Glacial Maximum to present-day. The model includes a fully dynamic, primitive equation atmosphere (the Reading IGCM), computed vegetation (TRIFFID), and a slab-ocean and seaice. The atmospheric model is more akin to a low-resolution GCM than traditional EMICS, and yet is fast enough for long ensemble simulations to be carried out. The model is tuned in a purely objective manner, using a genetic algorithm, which perturbs 30 tunable paramters in the model to find the best fit to a prescribed pre-industrial climate.The control deglaciation experiment has good agreement with data at the Last glacial Maximum and mid-Holocene. The deglaciation ensembles are over initial conditions, physical processes, and tunable model parameters. The ice-sheets are prescribed, and changes in oceanic heat transport are neglected, and yet the model exhibits rapid transitions in many of the ensemble members. These are attributable to the interaction of the dynamic atmosphere with the sea-ice, and are not observed when the ocean and sea-ice surface temperatures are prescribed. The timing of these transitions is sensitive to the initial conditions, pointing to the chaotic nature of the climate system.The simulations have been carried out making use of GRID technologies, developed as part of the GENIE project

    Global patterns in the divergence between phylogenetic diversity and species richness in terrestrial birds

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    Aim The conservation value of sites is often based on species richness (SR).However, metrics of phylogenetic diversity (PD) reflect a community’s evolu-tionary potential and reveal the potential for additional conservation valueabove that based purely on SR. Although PD is typically correlated with SR,localized differences in this relationship have been found in different taxa.Here, we explore geographical variation in global avian PD. We identify wherePD is higher or lower than expected (from SR) and explore correlates of thosedifferences, to find communities with high irreplaceability, in terms of theuniqueness of evolutionary histories.Location Global terrestrial.Methods Using comprehensive avian phylogenies and global distributionaldata for all extant birds, we calculated SR and Faith’s PD, a widely appliedmeasure of community PD, across the terrestrial world. We modelled the rela-tionship between avian PD for terrestrial birds and its potential environmentalcorrelates. Analyses were conducted at a global scale and also for individualbiogeographical realms. Potential explanatory variables of PD included SR,long-term climate stability, climatic diversity (using altitudinal range as aproxy), habitat diversity and proximity to neighbouring realms.Results We identified areas of high and low relative PD (rPD; PD relative tothat expected given SR). Areas of high rPD were associated with deserts andislands, while areas of low rPD were associated with historical glaciation. Ourresults suggest that rPD is correlated with different environmental variables indifferent parts of the world.Main conclusions There is geographical variation in avian rPD, much ofwhich can be explained by putative drivers. However, the importance of thesedrivers shows pronounced regional variation. Moreover, the variation in avianrPD differs substantially from patterns found for mammals and amphibians.We suggest that PD adds additional insights about the irreplaceability of com-munities to conventional metrics of biodiversity based on SR, and could beusefully included in assessments of site valuation and prioritizatio

    Response of methane emissions from wetlands to the Last Glacial Maximum and an idealized Dansgaard-Oeschger climate event: insights from two models of different complexity

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    The role of different sources and sinks of CH<sub>4</sub> in changes in atmospheric methane ([CH<sub>4</sub>]) concentration during the last 100 000 yr is still not fully understood. In particular, the magnitude of the change in wetland CH<sub>4</sub> emissions at the Last Glacial Maximum (LGM) relative to the pre-industrial period (PI), as well as during abrupt climatic warming or Dansgaard–Oeschger (D–O) events of the last glacial period, is largely unconstrained. In the present study, we aim to understand the uncertainties related to the parameterization of the wetland CH<sub>4</sub> emission models relevant to these time periods by using two wetland models of different complexity (SDGVM and ORCHIDEE). These models have been forced by identical climate fields from low-resolution coupled atmosphere–ocean general circulation model (FAMOUS) simulations of these time periods. Both emission models simulate a large decrease in emissions during LGM in comparison to PI consistent with ice core observations and previous modelling studies. The global reduction is much larger in ORCHIDEE than in SDGVM (respectively −67 and −46%), and whilst the differences can be partially explained by different model sensitivities to temperature, the major reason for spatial differences between the models is the inclusion of freezing of soil water in ORCHIDEE and the resultant impact on methanogenesis substrate availability in boreal regions. Besides, a sensitivity test performed with ORCHIDEE in which the methanogenesis substrate sensitivity to the precipitations is modified to be more realistic gives a LGM reduction of −36%. The range of the global LGM decrease is still prone to uncertainty, and here we underline its sensitivity to different process parameterizations. Over the course of an idealized D–O warming, the magnitude of the change in wetland CH<sub>4</sub> emissions simulated by the two models at global scale is very similar at around 15 Tg yr<sup>−1</sup>, but this is only around 25% of the ice-core measured changes in [CH<sub>4</sub>]. The two models do show regional differences in emission sensitivity to climate with much larger magnitudes of northern and southern tropical anomalies in ORCHIDEE. However, the simulated northern and southern tropical anomalies partially compensate each other in both models limiting the net flux change. Future work may need to consider the inclusion of more detailed wetland processes (e.g. linked to permafrost or tropical floodplains), other non-wetland CH<sub>4</sub> sources or different patterns of D–O climate change in order to be able to reconcile emission estimates with the ice-core data for rapid CH<sub>4</sub> events

    Uncertainties in the modelled CO2 threshold for Antarctic glaciation

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    A frequently cited atmospheric CO2 threshold for the onset of Antarctic glaciation of ∼780 ppmv is based on the study of DeConto and Pollard (2003) using an ice sheet model and the GENESIS climate model. Proxy records suggest that atmospheric CO2 concentrations passed through this threshold across the Eocene-Oligocene transition ∼34 Ma. However, atmospheric CO2 concentrations may have been close to this threshold earlier than this transition, which is used by some to suggest the possibility of Antarctic ice sheets during the Eocene. Here we investigate the climate model dependency of the threshold for Antarctic glaciation by performing offline ice sheet model simulations using the climate from 7 different climate models with Eocene boundary conditions (HadCM3L, CCSM3, CESM1.0, GENESIS, FAMOUS, ECHAM5 and GISS-ER). These climate simulations are sourced from a number of independent studies, and as such the boundary conditions, which are poorly constrained during the Eocene, are not identical between simulations. The results of this study suggest that the atmospheric CO2 threshold for Antarctic glaciation is highly dependent on the climate model used and the climate model configuration. A large discrepancy between the climate model and ice sheet model grids for some simulations leads to a strong sensitivity to the lapse rate parameter

    New developments in CLAMP: Calibration using global gridded meteorological data

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    Climate Leaf Analysis Multivariate Program (CLAMP) is a versatile technique for obtaining quantitative estimates for multiple terrestrial palaeoclimate variables from woody dicot leaf assemblages. To date it has been most widely applied to the Late Cretaceous and Tertiary of the mid- to high latitudes because of concerns over the relative dearth of calibration sites in modern low-latitude warm climates, and the loss of information associated with the lack of marginal teeth on leaves in paratropical to tropical vegetation. This limits CLAMP's ability to quantify reliably climates at low latitudes in greenhouse worlds of the past. One of the reasons for the lack of CLAMP calibration samples from warm environments is the paucity of climate stations close to potential calibration vegetation sites at low latitudes. Agriculture and urban development have destroyed most lowland sites and natural vegetation is now largely confined to mountainous areas where climate stations are few and climatic spatial variation is high due to topographic complexity. To attempt to overcome this we have utilised a 0.5° × 0.5° grid of global interpolated climate data based on the data set of New et al. (1999) supplemented by the ERA40 re-analysis data for atmospheric temperature at upper levels. For each location, the 3-D climatology of temperature from the ECMWF re-analysis project was used to calculate the mean lower tropospheric lapse rate for each month of the year. The gridded data were then corrected to the altitude of the plant site using the monthly lapse rates. Corrections for humidity were also made. From this the commonly returned CLAMP climate variables were calculated. A bi-linear interpolation scheme was then used to calculate the climate parameters at the exact lat/long of the site. When CLAMP analyses using the PHYSG3BR physiognomic data calibrated with the climate station based MET3BR were compared to analyses using the gridded data at the same locations (GRIDMET3BR), the results were indistinguishable in that they fell within the range of statistical uncertainty determined for each analysis. This opens the way to including natural vegetation anywhere in the world irrespective of the proximity of a meteorological station

    Contrasting the Penultimate Glacial Maximum and the Last Glacial Maximum (140 and 21 ka) using coupled climate–ice sheet modelling

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    The configuration of the Northern Hemisphere ice sheets during the Penultimate Glacial Maximum differed to the Last Glacial Maximum. However, the reasons for this are not yet fully understood. These differences likely contributed to the varied deglaciation pathways experienced following the glacial maxima and may have had consequences for the interglacial sea level rise. To understand the differences between the North American Ice Sheet at the Last and Penultimate glacial maxima (21 and 140 ka), we perform two perturbed-physics ensembles of 62 simulations using a coupled atmosphere–ice sheet model, FAMOUS-ice, with prescribed surface ocean conditions, in which the North American and Greenland ice sheets are dynamically simulated with the Glimmer ice sheet model. We apply an implausibility metric to find ensemble members that match reconstructed ice extent and volumes at the Last and Penultimate glacial maxima. We use a resulting set of “plausible” parameters to perform sensitivity experiments to decompose the role of climate forcings (orbit, greenhouse gases) and initial conditions on the final ice sheet configurations. This confirms that the initial ice sheet conditions used in the model are extremely important in determining the difference in final ice volumes between both periods due to the large effect of the ice–albedo feedback. In contrast to evidence of a smaller Penultimate North American Ice Sheet, our results show that the climate boundary conditions at these glacial maxima, if considered in isolation, imply a larger Penultimate Glacial Maximum North American Ice Sheet than at the Last Glacial Maximum by around 6 m sea level equivalent. This supports the notion that the growth of the ice sheet prior to the glacial maxima is key in explaining the differences in North American ice volume
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