Statistische Trendanalysen bei marinen Monitoringdaten—Aktuelle Diskussionen

Ocean Dynamics - Ausgangspunkt der vorliegenden Arbeit sind Untersuchungen der ICES-Arbeitsgruppe WGSAEM zur Vereinheitlichung der Trendanalyse von Monitoringzeitreihen. Dabei stehen die folgenden...     

Limitations of Majority Agreement in Crowdsourced Image Interpretation

Crowdsourcing can efficiently complete tasks that are difficult to automate, but the quality of crowdsourced data is tricky to evaluate. Algorithms to grade volunteer work often assume that all tasks are similarly difficult, an assumption that is frequently false. We use a cropland identification game with over 2,600 participants and 165,000 unique tasks to investigate how best to evaluate the difficulty of crowdsourced tasks and to what extent this is possible based on volunteer responses alone. Inter‐volunteer agreement exceeded 90% for about 80% of the images and was negatively correlated with volunteer‐expressed uncertainty about image classification. A total of 343 relatively difficult images were independently classified as cropland, non‐cropland or impossible by two experts. The experts disagreed weakly (one said impossible while the other rated as cropland or non‐cropland) on 27% of the images, but disagreed strongly (cropland vs. non‐cropland) on only 7%. Inter‐volunteer disagreement increased significantly with inter‐expert disagreement. While volunteers agreed with expert classifications for most images, over 20% would have been mis‐categorized if only the volunteers’ majority vote was used. We end with a series of recommendations for managing the challenges posed by heterogeneous tasks in crowdsourcing campaigns.     

Satellite-based terrestrial production efficiency modeling

Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research.     

KGI-XGIS supporting decision making with knowledge-based techniques

The concept of the King George Island Expert GIS (KGI-XGIS) is introduced. KGI-XGIS is a combination of a rule-based expert system and a GIS meant to form an intelligent spatial decision support system. The system provides the spatial knowledge necessary for the environmental impact assessment process as dictated by the ‘Madrid Protocol’ for King George Island (South Shetland Islands, Antarctica). It also serves as information system to the scientific user community. Topographic maps, remote sensing data, thematic maps based on field surveys and other digital data form the input data to the GIS. Given the sparseness of the available data these must be combined and used in the most efficient way. Therefore expert knowledge of different domains will be coded into a rule-based expert system which is coupled to the GIS. To handle the expert knowledge and the spatial data of different types and different quality the KGI-XGIS incorporates knowledge-based techniques and fuzzy reasoning. The selection of a camp site on the ice free area of Fildes Peninsula and data quality management are used as two examples to demonstrate the capabilities of the system.     

Nonstationarity of turbulent heat fluxes at Summit,Greenland

Turbulence data collected over a total of 25 days during two summers are used to describe processes responsible for the nonstationarity of turbulent sensible heat fluxes at Summit, Greenland. A stationarity test shows that about 40% of the data are classified as nonstationary. Three main factors are explored to account for the large fraction of nonstationary runs: (1) intermittency of turbulence in stable conditions, (2) changes in net all-wave radiation in response to cloud forcing, and (3) diurnal trends in stability. A classification procedure that accounts for the intermittent nature of turbulence shows that during stable, nonstationary conditions 50% of the total sensible heat flux is realized in 22% of the sampling time. Intermittency often occurs at Summit during periods characterized by weak and irregular horizontal winds in combination with strong stability. Rapid changes in net all-wave radiation in response to cloud forcing results in nonstationarity during unstable conditions. Between 0930–1130 and 1900–1930 UTC turbulent heat fluxes are not only small in magnitude but also typically change sign, with nonstationarity during these periods often as high as 65%. These results should help resolve some of the present uncertainties in obtaining reliable fluxes at this site, in particular under stable atmospheric conditions.     

To what extent can a long-term temperature target guide near-term climate change commitments?

The question of appropriate timing and stringency of future greenhouse gas (GHG) emission reductions remains an issue in the discussion of mitigation responses to the climate change problem. It has been argued that our near-term action should be guided by a long-term vision for the climate, possibly a long-term temperature target. In this paper, we review proposals for long-term climate targets to avoid ‘dangerous’ climate change. Using probability estimates of climate sensitivity from the literature, we then generate probabilistic emissions scenarios that satisfy temperature targets of 2.0, 2.5, and 3.0°C above pre-industrial levels with no overshoot. Our interest is in the implications of these targets on abatement requirements over the next 50 years. If we allow global industrial GHG emissions to peak in 2025 at 14 GtCeq, and wish to achieve a 2.0°C target with at least 50% certainty, we find that the low sensitivity estimate in the literature suggests our industrial emissions must fall to 9 GtCeq by 2050: equal to the level in 2000. However, the average literature sensitivity estimate suggests the level must be less than 2 GtCeq; and in the high sensitivity case, the target is simply unreachable unless we allow for overshoot. Our results suggest that in light of the uncertainty in our knowledge of the climate sensitivity, a long-term temperature target (such as the 2.0°C target proposed by the European Commission) can provide limited guidance to near-term mitigation requirements.     

Comparison of an algebraic multigrid algorithm to two iterative solvers used for modeling ground water flow and transport

Numerical solution of large-scale ground water flow and transport problems is often constrained by the convergence behavior of the iterative solvers used to solve the resulting systems of equations. We demonstrate the ability of an algebraic multigrid algorithm (AMG) to efficiently solve the large, sparse systems of equations that result from computational models of ground water flow and transport in large and complex domains. Unlike geometric multigrid methods, this algorithm is applicable to problems in complex flow geometries, such as those encountered in pore-scale modeling of two-phase flow and transport. We integrated AMG into MODFLOW 2000 to compare two- and three-dimensional flow simulations using AMG to simulations using PCG2, a preconditioned conjugate gradient solver that uses the modified incomplete Cholesky preconditioner and is included with MODFLOW 2000. CPU times required for convergence with AMG were up to 140 times faster than those for PCG2. The cost of this increased speed was up to a nine-fold increase in required random access memory (RAM) for the three-dimensional problems and up to a four-fold increase in required RAM for the two-dimensional problems. We also compared two-dimensional numerical simulations of steady-state transport using AMG and the generalized minimum residual method with an incomplete LU-decomposition preconditioner. For these transport simulations, AMG yielded increased speeds of up to 17 times with only a 20% increase in required RAM. The ability of AMG to solve flow and transport problems in large, complex flow systems and its ready availability make it an ideal solver for use in both field-scale and pore-scale modeling.     

Characteristics of Stable Flows over Southern Greenland

The main characteristic features of stable atmospheric flows over a large mountain plateau are summarised and then compared with mesoscale and synoptic scale numerical simulation, meteorological analysis, satellite imagery, and surface observations for the cases of flows over Southern Greenland for four wind directions. The detailed features are identified using the concepts and scaling of stably stratified flow over large mountains with variations in surface roughness, elevation, and heating. For westerly and easterly winds detached jets form at the southern tip, where coastal jets converge, which propagate large distances across the ocean. Near coasts katabatic winds can combine with barrier jets and wake flows generated by synoptic winds. Note how the approach flow rises/falls over southern Greenland for easterly/westerly winds, leading in both cases to more cloud on the western side. Some conclusions are drawn about the large-scale influences of these flows; detached jets in the atmosphere; air-sea interaction; formation of low pressure systems. For accurate simulations of these flows, mesoscale models are necessary with resolutions of order of 20 km or less.