Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing

Anthropogenic emissions of greenhouse gases such as CO2 and N2O impinge on the Earth system, which in turn modulates atmospheric greenhouse gas concentrations. The underlying feedback mechanisms are complex and, at times, counterintuitive. So-called Earth system models have recently matured to standard tools tailored to assess these feedback mechanisms in a warming world. Applications for these models range from being targeted at basic process understanding to the assessment of geo-engineering options. A problem endemic to all these applications is the need to estimate poorly known model parameters, specifically for the biogeochemical component, based on observational data (e.g., nutrient fields). In the present study, we illustrate with an Earth system model that through such an approach biases and other model deficiencies in the physical ocean circulation model component can reciprocally compensate for biases in the pelagic biogeochemical model component (and vice versa). We present two model configurations that share a remarkably similar steady state (based on ad hoc measures) when driven by historical boundary conditions, even though they feature substantially different configurations (parameter sets) of ocean mixing and biogeochemical cycling. When projected into the future the similarity between the model responses breaks. Metrics such as changes in total oceanic carbon content and suboxic volume diverge between the model configurations as the Earth warms. Our results reiterate that advancing the understanding of oceanic mixing processes will reduce the uncertainty of future projections of oceanic biogeochemical cycles. Related to the latter, we suggest that an advanced understanding of oceanic biogeochemical cycles can be used for advancements in ocean circulation modules.</p

Understanding Malicious Behavior in Crowdsourcing Platforms: The Case of Online Surveys.

Crowdsourcing is increasingly being used as a means to tackle problems requiring human intelligence. With the ever-growing worker base that aims to complete microtasks on crowdsourcing platforms in exchange for financial gains, there is a need for stringent mechanisms to prevent exploitation of deployed tasks. Quality control mechanisms need to accommodate a diverse pool of workers, exhibiting a wide range of behavior. A pivotal step towards fraud-proof task design is understanding the behavioral patterns of microtask workers. In this paper, we analyze the prevalent malicious activity on crowdsourcing platforms and study the behavior exhibited by trustworthy and untrustworthy workers, particularly on crowdsourced surveys. Based on our analysis of the typical malicious activity, we define and identify different types of workers in the crowd, propose a method to measure malicious activity, and finally present guidelines for the efficient design of crowdsourced surveys

Mapping manifestations of parametric uncertainty in projected pelagic oxygen concentrations back to contemporary local model fidelity

Pelagic biogeochemical models (BGCMs) have matured into generic components of Earth System Models. BGCMs mimic the effects of marine biota on oceanic nutrient, carbon and oxygen cycles. They rely on parameters that are adjusted to match observed conditions. Such parameters are key to determining the models’ responses to changing environmental conditions. However, many of these parameters are difficult to constrain and constitute a major source of uncertainty in BGCM projections. Here we use, for the first time, variance-based sensitivity analyses to map BGCM parameter uncertainties onto their respective local manifestation in model entities (such as oceanic oxygen concentrations) for both contemporary climate and climate projections. The mapping effectively relates local uncertainties of projections to the uncertainty of specific parameters. Further, it identifies contemporary benchmarking regions, where the uncertainties of specific parameters manifest themselves, thereby facilitating an effective parameter refinement and a reduction of the associated uncertainty. Our results demonstrate that the parameters that are linked to uncertainties in projections may differ from those parameters that facilitate model conformity with present-day observations. In summary, we present a practical approach to the general question of where present-day model fidelity may be indicative for reliable projections

Calibrating and testing tissue equivalent proportional counters with 37Ar

A method for testing and calibrating tissue equivalent proportional counters with37Ar is described.37Ar is produced by exposure of argon in its normal isotope composition to thermal neutrons. It is shown that - up to volume ratios of 0.01 of argon to the tissue equivalent gas - there is no appreciable effect of the argon admixture on the function of the proportional counter. Conventional calibration methods with characteristic x-rays or with -particles require modifications of the detectors, and they test only small sub-volumes in the counters. In contrast, argon permits calibrations and tests of the resolution that are representative for the entire counter volume and that do not require changes in detector construction. The method is equally applicable to multi-element proportional counters; it is here exemplified by its application to a long cylindrical counter of simplified design that is part of such a multi-element configuration

Interoperable multimedia metadata through similarity-based semantic web service discovery

The increasing availability of multimedia (MM) resources, Web services as well as content, on the Web raises the need to automatically discover and process resources out of distributed repositories. However, the heterogeneity of applied metadata schemas and vocabularies – ranging from XML-based schemas such as MPEG-7 to formal knowledge representation approaches – raises interoperability problems. To enable MM metadata interoperability by means of automated similarity-computation, we propose a hybrid representation approach which combines symbolic MM metadata representations with a grounding in so-called Conceptual Spaces (CS). In that, we enable automatic computation of similarities across distinct metadata vocabularies and schemas in terms of spatial distances in shared CS. Moreover, such a vector-based approach is particularly well suited to represent MM metadata, given that a majority of MM parameters is provided in terms of quantified metrics. To prove the feasibility of our approach, we provide a prototypical implementation facilitating similarity-based discovery of publicly available MM services, aiming at federated MM content retrieval out of heterogeneous repositories

Major role of the equatorial current system in setting oxygen levels in the eastern tropical Atlantic Ocean: a high-resolution model study

Understanding the causes of the observed expansion of tropical ocean's oxygen minimum zones (OMZs) is hampered by large biases in the representation of oxygen distribution in climate models, pointing to incorrectly represented mechanisms. Here we assess the oxygen budget in a global biogeochemical circulation model, focusing on the Atlantic Ocean. While a coarse (0.5°) configuration displays the common bias of too large and too intense OMZs, the oxygen concentration in an eddying (0.1°) configuration is higher and closer to observations. This improvement is traced to a stronger oxygen supply by a more realistic representation of the equatorial and off-equatorial undercurrents, outweighing the concurrent increase in oxygen consumption associated with the stronger nutrient supply. The sensitivity of the eastern tropical Atlantic oxygen budget to the equatorial current intensity suggests that temporal changes in the eastward oxygen transport from the well-oxygenated western boundary region might partly explain variations in the OMZs

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of plant functional types (PFTs). We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (specific leaf area [SLA], N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (dark respiration [R-d], maximum RuBisCo carboxylation rate [V-c,V-max], maximum electron transport rate [J(max)]) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, this covariance was an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.Environmental Biolog

Reanalysis in Earth System Science: Towards Terrestrial Ecosystem Reanalysis

A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation. High computational costs for modelled processes and assimilation algorithms has led to Earth system specific reanalysis products for the atmosphere, the ocean and the land separately. Recent developments include the advanced uncertainty quantification and the generation of biogeochemical reanalysis for land and ocean. Here, we review atmospheric and oceanic reanalyses, and more in detail biogeochemical ocean and terrestrial reanalyses. In particular, we identify land surface, hydrologic and carbon cycle reanalyses which are nowadays produced in targeted projects for very specific purposes. Although a future joint reanalysis of land surface, hydrologic and carbon processes represents an analysis of important ecosystem variables, biotic ecosystem variables are assimilated only to a very limited extent. Continuous data sets of ecosystem variables are needed to explore biotic-abiotic interactions and the response of ecosystems to global change. Based on the review of existing achievements, we identify five major steps required to develop terrestrial ecosystem reanalysis to deliver continuous data streams on ecosystem dynamics

MEMS Technologies for Energy Harvesting

The objective of this chapter is to introduce the technology of Microelectromechanical Systems, MEMS, and their application to emerging energy harvesting devices. The chapter begins with a general introduction to the most common MEMS fabrication processes. This is followed with a survey of design mechanisms implemented in MEMS energy harvesters to provide nonlinear mechanical actuations. Mechanisms to produce bistable potential will be studied, such as introducing fixed magnets, buckling of beams or using slightly slanted clamped-clamped beams. Other nonlinear mechanisms are studied such as impact energy transfer, or the design of nonlinear springs. Finally, due to their importance in the field of MEMS and their application to energy harvesters, an introduction to actuation using piezoelectric materials is given. Examples of energy harvesters found in the literature using this actuation principle are also presented