Possible causes of data model discrepancy in the temperature history of the last Millennium

Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role

Collaborative Aircraft Engine Preliminary Design using a Virtual Engine Platform, Part A: Architecture and Methodology

As in many other industries, the sector of aircraft engines and gas turbines is also undergoing a change towards digitalization. The intention is to make digital technologies applicable over the entire life cycle of the product and thus improve planning, design, construction, assembly, operation, and maintenance. Intelligent digitalization technologies like the digital thread or digital twin will drastically change engineering and construction processes. Consequently, the preliminary aircraft engine design must also be embedded into the context of digitalization. As part of the projects PEGASUS and PERFECT, the German Aerospace Center (DLR) has started the development of the virtual engine platform GTlab (Gas Turbine Laboratory). Its modular architecture ensures a high degree of usability, expandability, and flexibility for the design and assessment of innovative next generation engine and gas turbine concepts. The purpose of this paper is to present the most important aspects of the GTlab framework and how they contribute to meet the requirements of preliminary aircraft engine design in the context of digitalization. A central topic is the digital representation of the engine system, which is realized by a central data model approach. This includes the geometric description of all engine components, as well as additional data such as thermodynamics, aerodynamics, structural characteristics and mass breakdown. In addition, the central data model enables an efficient management of the intricate data flow and the extensive amount of data transferred between the different disciplines and fidelity levels during the aircraft engine design. Further functionalities of the GTlab framework include the automated generation of 3-D geometries by means of a CAD kernel interface, the acquisition of material data via a material database and a standardized gas model interface. Besides the core functionalities, GTlab includes three major modules for the preliminary aircraft engine design from 0-D-performance up to 3-D. The detailed collaborative predesign proces by means of the framework is presented in part B, exemplary for a ultra high bypass turbofan suited to a middle of the market aircraft configuration

Data from: Study "Red Knot geolocator tracking New Zealand 2013"

The pace and scale of environmental change represent major challenges to many organisms. Animals that move long distances, such as migratory birds, are especially vulnerable to change since they need chains of intact habitat along their migratory routes. Estimating the resilience of such species to environmental changes assists in targeting conservation efforts. We developed a migration modeling framework to predict past (1960s), present (2010s), and future (2060s) optimal migration strategies across five shorebird species (Scolopacidae) within the East Asian-Australasian Flyway, which has seen major habitat deterioration and loss over the last century, and compared these predictions to empirical tracks from the present. Our model captured the migration strategies of the five species and identified the changes in migrations needed to respond to habitat deterioration and climate change. Notably, the larger species, with single or few major stopover sites, need to establish new migration routes and strategies, while smaller species can buffer habitat loss by redistributing their stopover areas to novel or less-used sites. Comparing model predictions with empirical tracks also indicates that larger species with the stronger need for adaptations continue to migrate closer to the optimal routes of the past, before habitat deterioration accelerated. Our study not only quantifies the vulnerability of species in the face of global change but also explicitly reveals the extent of adaptations required to sustain their migrations. This modeling framework provides a tool for conservation planning that can accommodate the future needs of migratory species

Data from: Study "Bar-tailed Godwit geolocator tracking New Zealand 2013-2014"

The pace and scale of environmental change represent major challenges to many organisms. Animals that move long distances, such as migratory birds, are especially vulnerable to change since they need chains of intact habitat along their migratory routes. Estimating the resilience of such species to environmental changes assists in targeting conservation efforts. We developed a migration modeling framework to predict past (1960s), present (2010s), and future (2060s) optimal migration strategies across five shorebird species (Scolopacidae) within the East Asian-Australasian Flyway, which has seen major habitat deterioration and loss over the last century, and compared these predictions to empirical tracks from the present. Our model captured the migration strategies of the five species and identified the changes in migrations needed to respond to habitat deterioration and climate change. Notably, the larger species, with single or few major stopover sites, need to establish new migration routes and strategies, while smaller species can buffer habitat loss by redistributing their stopover areas to novel or less-used sites. Comparing model predictions with empirical tracks also indicates that larger species with the stronger need for adaptations continue to migrate closer to the optimal routes of the past, before habitat deterioration accelerated. Our study not only quantifies the vulnerability of species in the face of global change but also explicitly reveals the extent of adaptations required to sustain their migrations. This modeling framework provides a tool for conservation planning that can accommodate the future needs of migratory species