4 resultados para SENSITIVITY ANALYSIS

em Publishing Network for Geoscientific


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The Marine Isotope Stage (MIS) 11 (424-374 ka) was characterized by a protracted deglaciation and an unusually long climatic optimum. It remains unclear to what degree the climate development during this interglacial reflects the unusually weak orbital forcing or greenhouse gas trends. Previously, arguments about the duration and timing of the MIS11 climatic optimum and about the pace of the deglacial warming were based on a small number of key records, which appear to show regional differences. In order to obtain a global signal of climate evolution during MIS11, we compiled a database of 78 sea surface temperature (SST) records from 57 sites spanning MIS11, aligned these individually on the basis of benthic (N = 28) or planktonic (N = 31) stable oxygen isotope curves to a common time frame and subjected 48 of them to an empirical orthogonal function (EOF) analysis. The analysis revealed a high commonality among all records, with the principal SST trend explaining almost 49% of the variability. This trend indicates that on the global scale, the surface ocean underwent rapid deglacial warming during Termination V, in pace with carbon dioxide rise, followed by a broad SST optimum centered at ~410 kyr. The second EOF, which explained ~18% of the variability, revealed the existence of a different SST trend, characterized by a delayed onset of the temperature optimum during MIS11 at ~398 kyr, followed by a prolonged warm period lasting beyond 380 kyr. This trend is most consistently manifested in the mid-latitude North Atlantic and Mediterranean Sea and is here attributed to the strength of the Atlantic meridional overturning circulation. A sensitivity analysis indicates that these results are robust to record selection and to age-model uncertainties of up to 3-6 kyr, but more sensitive to SST seasonal attribution and SST uncertainties >1 °C. In order to validate the CCSM3 (Community Climate System Model, version 3) predictive potential, the annual and seasonal SST anomalies recorded in a total of 74 proxy records were compared with runs for three time slices representing orbital configuration extremes during the peak interglacial of MIS11. The modeled SST anomalies are characterized by a significantly lower variance compared to the reconstructions. Nevertheless, significant correlations between proxy and model data are found in comparisons on the seasonal basis, indicating that the model captures part of the long-term variability induced by astronomical forcing, which appears to have left a detectable signature in SST trends.

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State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80-90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined 'true' state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations.

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Siberian boreal forests are expected to expand northwards in the course of global warming. However, processes of the treeline ecotone transition, as well astiming and related climate feedbacks are still not understood. Here, we present 'Larix Vegetation Simulator' LAVESI, an individual-based spatially-explicit model that can simulate Larix gmelinii (RUPR.) RUPR. stand dynamics in an attempt to improve our understanding about past and future treeline movements under changing climates. The relevant processes (growth, seed production and dispersal, establishment and mortality) are incorporated and adjusted to observation data mainly gained from the literature. Results of a local sensitivity analysis support the robustness of the model's parameterization by giving relatively small sensitivity values. We tested the model by simulating tree stands under modern climate across the whole Taymyr Peninsula, north-central Siberia (c. 64-80° N; 92-119° E). We find tree densities similar to observed forests in the northern to mid-treeline areas, but densities are overestimated in the southern parts of the simulated region. Finally, from a temperature-forcing experiment, we detect that the responses of tree stands lag the hypothetical warming by several decades, until the end of 21st century. With our simulation experiments we demonstrate that the newly-developed model captures the dynamics of the Siberian latitudinal treeline.

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The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to observations of the solute breakthrough in column outflow experiments. This parameters uncertainty can be approached by the application of multiple experimental designs such as column experiments in open-flow mode and the recently proposed closed-flow mode. Latter are characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow. Depending on the experimental conditions, the solute concentration in the solution supply vessel and the effluent follows a damped sinusoidal oscillation. As a result, the closed-flow experiment provides additional observables in the breakthrough curve. The evaluation of these emergent features allows intrinsic control over boundary conditions and impacts the uncertainty of parameters in inverse modeling. We present a comprehensive sensitivity analysis to illustrate the potential application of closed-flow experiments. We show that the sensitivity with respect to the apparent dispersion can be controlled by the experimenter leading to a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude for optimal settings. With these finding we are also able to reduce the equifinality found for situations, where rate-limited interactions impede a proper determination of the apparent dispersion and rate coefficients. Furthermore, we show the expected breakthrough curve for equilibrium and kinetic sorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. This renders the closed-flow mode a useful complementary approach to classical column experiments.