Consistent meteorological/oceanographic datasets derived from regional reanalyses and climate cha... more Consistent meteorological/oceanographic datasets derived from regional reanalyses and climate change projections prove particularly useful for coastal defense and offshore industry
This is a very nice paper on dispersion characteristics in German Bight. What makes this paper qu... more This is a very nice paper on dispersion characteristics in German Bight. What makes this paper quite special is the existence of offshore wind farms (OWFs) in the region, even though these effects do not really show up in the results. Also, the authors did an excellent job in executing the paper as well discussing at length with respect to all previous work (maybe with the exception of some, as suggested below). Some of this discussion is fueled by the inconclusive nature of the results, which seem to be mainly due to the small number of drifters; something that could be improved in the future. Nevertheless, overall it is a great, careful study and I recommend acceptance subject to possible modification as per my minor comments below:
We present a case study for Bayesian analysis and proper representation of distributions and depe... more We present a case study for Bayesian analysis and proper representation of distributions and dependence among parameters when calibrating process-oriented environmental models. A simple water quality model for the Elbe River (Germany) is referred to as an example, but the approach is applicable to a wide range of environmental models with time-series output. Model parameters are estimated by Bayesian inference via Markov Chain Monte Carlo (MCMC) sampling. While the best-fit solution matches usual least-squares model calibration (with a penalty term for excessive parameter values), the Bayesian approach has the advantage of yielding a joint probability distribution for parameters. This posterior distribution encompasses all possible parameter combinations that produce a simulation output that fits observed data within measurement and modeling uncertainty. Bayesian inference further permits the introduction of prior knowledge, e.g., positivity of certain parameters. The estimated dist...
A 47-yr (1958-2004) model simulation has been analyzed to identify changes of the southern North ... more A 47-yr (1958-2004) model simulation has been analyzed to identify changes of the southern North Sea hydrodynamic regime in the past. A time series analysis revealed time points of changes in volume transports which correspond to recently described changes in the North Sea ecosystem (‘regime shifts’). The strengths of these hydrodynamic changes are shown to vary on a regional scale. Being interested in the analysis of long-term time series (starting in 1962) of hydrophysical and biological parameters measured at the island of Helgoland (54°11.3’ N, 7°54.0’ E, German Bight) we studied seasonal and interannual variations of the North Sea hydrodynamic regime with respect to their effects on the Helgoland area. An Empirical Orthogonal Function (EOF) analysis of spatial patterns of passive tracer Lagrangian transports has been carried out to describe the temporal variability of water mass advection. It could be shown that the southern inflow to the North Sea (via the English Channel) has...
We address the analysis and proper representation of posterior dependence among parameters obtain... more We address the analysis and proper representation of posterior dependence among parameters obtained from model calibration. A simple water quality model for the Elbe River (Germany) is referred to as an example. The joint posterior distribution of six model parameters is estimated by Markov Chain Monte Carlo sampling based on a quadratic likelihood function. The estimated distribution shows to which extent model parameters are controlled by observations, highlighting issues that cannot be settled unless more information becomes available. In our example, some vagueness occurs due to problems in distinguishing between the effects of either growth limitation by lack of silica or a temperature dependent algal loss rate. Knowing such indefiniteness of the model structure is crucial when the model is to be used in support of management options. Bayesian network technology can be employed to convey this information in a transparent way.
Abstract Chemical substances of either anthropogenic or natural origin affect air quality and, as... more Abstract Chemical substances of either anthropogenic or natural origin affect air quality and, as a consequence, also the health of the population. Therefore, there is a high demand for reliable air quality scenarios that can support possible management decisions. However, generating long term assessments of air quality assuming different emission scenarios is still a great challenge when using detailed atmospheric chemistry models. In this study, we test machine learning technique based on neural networks (NN) to emulate process-oriented modeling outcomes. A successfully calibrated NN might estimate concentrations of chemical substances in the air several orders faster than the original model and with reasonably small errors. We designed a simple recurrent 3-layer NN to reproduce daily mean concentrations of NO2, SO2 and C2H6 over Europe as simulated by the Community Multiscale Air Quality model (CMAQ). The general structure of the NN can be shown to approximate a continuity equation. Inputs of the network are daily mean meteorological state variables, taken from the climate model COSMO-CLM. The proposed NN emulates CMAQ outputs with an error not exceeding the difference between CMAQ and other known chemical transport models.
Blooming Succession Algal blooms in the ocean will trigger a succession of microbial predators an... more Blooming Succession Algal blooms in the ocean will trigger a succession of microbial predators and scavengers. Teeling et al. (p. 608 ) used a combination of microscopy, metagenomics, and metaproteomics to analyze samples from a North Sea diatom bloom over time. Distinct steps of polysaccharide degradation and carbohydrate uptake could be assigned to clades of Flavobacteria and Gammaproteobacteria, which differ profoundly in their transporter profiles and their uptake systems for phosphorus. The phytoplankton/bacterioplankton coupling in coastal marine systems is of crucial importance for global carbon cycling. Bacterioplankton clade succession following phytoplankton blooms may be predictable enough that it can be included in models of global carbon cycling.
One key challenge of marine monitoring programs is to reasonably combine information from differe... more One key challenge of marine monitoring programs is to reasonably combine information from different in situ observations spread in space and time. In that context, we suggest the use of Lagrangian transport simulations extending both forward and backward in time to identify the movements of water bodies from the time they were observed to the time of their synopsis. We present examples of how synoptic maps of salinity generated by this method support the identification and tracing of river plumes in coastal regions. We also demonstrate how we can use synoptic maps to delineate different water masses in coastal margins. These examples involve quasi-continuous observations of salinity taken along ferry routes. A third application is the synchronization of measurements between fixed stations and nearby moving platforms. Both observational platforms often see the same water body, but at different times. We demonstrate how the measurements from a fixed platform can be synchronized to mea...
Um zu verstehen, welche physikalischen Prozesse unser Modell beschreibt und welche es auser acht ... more Um zu verstehen, welche physikalischen Prozesse unser Modell beschreibt und welche es auser acht last, ist es interessant, Lorenz’s Rechnungen (1955/1967) zur global verfugbaren potentiellen Energie (APE) zu einem Vergleich heranzuziehen. Dabei soll immer gelten: ũ=u, ψ=ψ^, θ=θ.
Consistent meteorological/oceanographic datasets derived from regional reanalyses and climate cha... more Consistent meteorological/oceanographic datasets derived from regional reanalyses and climate change projections prove particularly useful for coastal defense and offshore industry
This is a very nice paper on dispersion characteristics in German Bight. What makes this paper qu... more This is a very nice paper on dispersion characteristics in German Bight. What makes this paper quite special is the existence of offshore wind farms (OWFs) in the region, even though these effects do not really show up in the results. Also, the authors did an excellent job in executing the paper as well discussing at length with respect to all previous work (maybe with the exception of some, as suggested below). Some of this discussion is fueled by the inconclusive nature of the results, which seem to be mainly due to the small number of drifters; something that could be improved in the future. Nevertheless, overall it is a great, careful study and I recommend acceptance subject to possible modification as per my minor comments below:
We present a case study for Bayesian analysis and proper representation of distributions and depe... more We present a case study for Bayesian analysis and proper representation of distributions and dependence among parameters when calibrating process-oriented environmental models. A simple water quality model for the Elbe River (Germany) is referred to as an example, but the approach is applicable to a wide range of environmental models with time-series output. Model parameters are estimated by Bayesian inference via Markov Chain Monte Carlo (MCMC) sampling. While the best-fit solution matches usual least-squares model calibration (with a penalty term for excessive parameter values), the Bayesian approach has the advantage of yielding a joint probability distribution for parameters. This posterior distribution encompasses all possible parameter combinations that produce a simulation output that fits observed data within measurement and modeling uncertainty. Bayesian inference further permits the introduction of prior knowledge, e.g., positivity of certain parameters. The estimated dist...
A 47-yr (1958-2004) model simulation has been analyzed to identify changes of the southern North ... more A 47-yr (1958-2004) model simulation has been analyzed to identify changes of the southern North Sea hydrodynamic regime in the past. A time series analysis revealed time points of changes in volume transports which correspond to recently described changes in the North Sea ecosystem (‘regime shifts’). The strengths of these hydrodynamic changes are shown to vary on a regional scale. Being interested in the analysis of long-term time series (starting in 1962) of hydrophysical and biological parameters measured at the island of Helgoland (54°11.3’ N, 7°54.0’ E, German Bight) we studied seasonal and interannual variations of the North Sea hydrodynamic regime with respect to their effects on the Helgoland area. An Empirical Orthogonal Function (EOF) analysis of spatial patterns of passive tracer Lagrangian transports has been carried out to describe the temporal variability of water mass advection. It could be shown that the southern inflow to the North Sea (via the English Channel) has...
We address the analysis and proper representation of posterior dependence among parameters obtain... more We address the analysis and proper representation of posterior dependence among parameters obtained from model calibration. A simple water quality model for the Elbe River (Germany) is referred to as an example. The joint posterior distribution of six model parameters is estimated by Markov Chain Monte Carlo sampling based on a quadratic likelihood function. The estimated distribution shows to which extent model parameters are controlled by observations, highlighting issues that cannot be settled unless more information becomes available. In our example, some vagueness occurs due to problems in distinguishing between the effects of either growth limitation by lack of silica or a temperature dependent algal loss rate. Knowing such indefiniteness of the model structure is crucial when the model is to be used in support of management options. Bayesian network technology can be employed to convey this information in a transparent way.
Abstract Chemical substances of either anthropogenic or natural origin affect air quality and, as... more Abstract Chemical substances of either anthropogenic or natural origin affect air quality and, as a consequence, also the health of the population. Therefore, there is a high demand for reliable air quality scenarios that can support possible management decisions. However, generating long term assessments of air quality assuming different emission scenarios is still a great challenge when using detailed atmospheric chemistry models. In this study, we test machine learning technique based on neural networks (NN) to emulate process-oriented modeling outcomes. A successfully calibrated NN might estimate concentrations of chemical substances in the air several orders faster than the original model and with reasonably small errors. We designed a simple recurrent 3-layer NN to reproduce daily mean concentrations of NO2, SO2 and C2H6 over Europe as simulated by the Community Multiscale Air Quality model (CMAQ). The general structure of the NN can be shown to approximate a continuity equation. Inputs of the network are daily mean meteorological state variables, taken from the climate model COSMO-CLM. The proposed NN emulates CMAQ outputs with an error not exceeding the difference between CMAQ and other known chemical transport models.
Blooming Succession Algal blooms in the ocean will trigger a succession of microbial predators an... more Blooming Succession Algal blooms in the ocean will trigger a succession of microbial predators and scavengers. Teeling et al. (p. 608 ) used a combination of microscopy, metagenomics, and metaproteomics to analyze samples from a North Sea diatom bloom over time. Distinct steps of polysaccharide degradation and carbohydrate uptake could be assigned to clades of Flavobacteria and Gammaproteobacteria, which differ profoundly in their transporter profiles and their uptake systems for phosphorus. The phytoplankton/bacterioplankton coupling in coastal marine systems is of crucial importance for global carbon cycling. Bacterioplankton clade succession following phytoplankton blooms may be predictable enough that it can be included in models of global carbon cycling.
One key challenge of marine monitoring programs is to reasonably combine information from differe... more One key challenge of marine monitoring programs is to reasonably combine information from different in situ observations spread in space and time. In that context, we suggest the use of Lagrangian transport simulations extending both forward and backward in time to identify the movements of water bodies from the time they were observed to the time of their synopsis. We present examples of how synoptic maps of salinity generated by this method support the identification and tracing of river plumes in coastal regions. We also demonstrate how we can use synoptic maps to delineate different water masses in coastal margins. These examples involve quasi-continuous observations of salinity taken along ferry routes. A third application is the synchronization of measurements between fixed stations and nearby moving platforms. Both observational platforms often see the same water body, but at different times. We demonstrate how the measurements from a fixed platform can be synchronized to mea...
Um zu verstehen, welche physikalischen Prozesse unser Modell beschreibt und welche es auser acht ... more Um zu verstehen, welche physikalischen Prozesse unser Modell beschreibt und welche es auser acht last, ist es interessant, Lorenz’s Rechnungen (1955/1967) zur global verfugbaren potentiellen Energie (APE) zu einem Vergleich heranzuziehen. Dabei soll immer gelten: ũ=u, ψ=ψ^, θ=θ.
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Natural Science Papers by Ulrich Callies
Papers by Ulrich Callies