997 research outputs found
Dr. J. C. Bluntschli
No full textNach d. Natur gez. v. Hans Notz ; Bei Fr. Hohe auf Stein gez. v. AtzingerZuschreibung an Johannes Notz ungesicher
Dr. J. C. Bluntschli
No full textNach d. Natur gez. v. Hans Notz ; Bei Fr. Hohe auf Stein gez. v. Atzinge
[Porträt des J. J. Steffan]
No full textPorträt des J. J. SteffanNach d. Nat. gez. v. J. Notz ; G. Balder lith.Faksimilierter Autograph unterhalb der Grafik auf der UnterlageDie Person kann nicht näher individualisiert werde
A 1-D modelling study of Arctic sea-ice salinity
No full textWe use a 1-D model to study how salinity evolves in Arctic sea ice. To do so,
we first explore how sea-ice surface melt and flooding can be incorporated
into the 1-D thermodynamic Semi-Adaptive
Multi-phase Sea-Ice Model (SAMSIM) presented by
Griewank and Notz (2013). We introduce flooding and a flushing parametrization
which treats sea ice as a hydraulic network of horizontal and vertical
fluxes. Forcing SAMSIM with 36 years of ERA-interim atmospheric reanalysis
data, we obtain a modelled Arctic sea-ice salinity that agrees well with
ice-core measurements. The simulations thus allow us to identify the main
drivers of the observed mean salinity profile in Arctic sea ice. Our results
show a 1.5–4 g kg−1 decrease of bulk salinity via gravity drainage after ice
growth has ceased and before flushing sets in, which hinders approximating
bulk salinity from ice thickness beyond the first growth season. In our
simulations, salinity interannual variability of first-year ice is mostly
restricted to the top 20 cm. We find that ice thickness, thermal resistivity,
freshwater column, and stored energy change by less than 5% on average when
the full salinity parametrization is replaced with a prescribed salinity
profile
Efficient block designs for comparing dual with single treatments.
No full textExperiments in blocks having two treatment factors are considered in which a particular treatment must be excluded. The work is motivated by medical trials of two drugs in which a double placebo cannot be administered on ethical grounds. The contrasts of interest compare the effects of having both treatment factor at non-zero labelled levels with the effects of having only one treatment factor at a non-zero labelled level. For nx2 experiments, a class of designs containing highly efficient members is identified and a lower bound on the efficiencies of designs in this class is derived. Tables of efficient designs are provided
When Will Arctic Sea Ice Be Gone?
No full textThe Arctic sea ice is the ice that is floating on the Arctic Ocean. In recent decades, this pack ice has been disappearing very rapidly. So the question arises when the Arctic sea ice will be completely gone. DIRK NOTZ has examined this using the Arctic summer sea ice in September as example. As he explains in this video, his research group combined satellite observations with model simulations and found a clear linear correlation between the loss of Arctic sea ice and carbon dioxide emissions. For each ton of CO2 we emit, we make about three square meters of Arctic sea ice disappear. From this linear relationship the researchers could extrapolate the amount of carbon dioxide that can still be emitted before the Arctic sea ice is completely gone in summers. For the first time, these findings present very intuitive numbers that make clear the impact every individual has on the global warming
Gründliche Anleitung zum Hopfenbau : Auf Veranstalten des Vereins für Land- und Gartenbau ; Mit lithogr. Abbildungen / herausgegeben von E. Regel, H. Notz, J. A. Kern und D. Freetz
No full textVorlageform der Veröffentlichungsangabe: Zürich, bei Orell, Füßli und Comp.Ill. (Lith.
Insights into brine dynamics and sea ice desalination from a 1-D model study of gravity drainage
No full textWe study gravity drainage using a new 1-D, multiphase sea ice model. A parametrization of gravity drainage based on the convective nature of gravity drainage is introduced, whose free parameters are determined by optimizing model output against laboratory measurements of sea ice salinity evolution. Optimal estimates of the free parameters as well as the parametrization performance remain stable for vertical grid resolutions from 1 to 30 mm. We find a strong link between sea ice growth rate and bulk salinity for constant boundary conditions but only a weak link for more realistic boundary conditions. We also demonstrate that surface warming can trigger brine convection over the whole ice layer. Over a growth season, replacing the convective parametrization with constant initial salinities leads to an overall 3% discrepancy of stored energy, thermal resistance, and salt release. We also derive from our convective parametrization a simplified, numerically cheap and stable gravity-drainage parametrization. This parametrization results in an approximately 1% discrepancy of stored energy, thermal resistance, and salt release compared to the convective parametrization. A similarly low discrepancy to our complex parametrization can be reached by simply prescribing a depth-dependent salinity profile. ©2013. American Geophysical Union. All Rights Reserved
Consistently estimating internal climate variability from climate model simulations
No full textAbstractThis paper introduces and applies a new method to consistently estimate internal climate variability for all models within a multi-model ensemble. The method regresses each model?s estimate of internal variability from the preindustrial control simulation on the variability derived from a model?s ensemble simulations, thus providing practical evidence of the quasi-ergodic assumption. The method allows one to test in a multi-model consensus view how the internal variability of a variable changes for different forcing scenarios. Applying the method to the CMIP5 model ensemble shows that the internal variability of global-mean surface air temperature remains largely unchanged for historical simulations and might decrease for future simulations with a large CO2 forcing. Regionally, the projected changes reveal likely increases in temperature variability in the tropics, subtropics and polar regions and extremely likely decreases in mid-latitudes. Applying the method to sea-ice volume and area shows that their internal variability decreases extremely likely or likely and proportionally to their mean state, except for Arctic sea-ice area, which shows no consistent change across models. For the evaluation of CMIP5 simulations of Arctic and Antarctic sea ice the method confirms that internal variability can explain most of the models? deviation from observed trends, but often not the models? deviation from the observed mean states. Our method benefits from a large number of models and long pre-industrial control simulations, but requires only a small number of ensemble simulations. The method allows for a consistent consideration of internal variability in multi-model studies and thus fosters our understanding of the role of internal variability in a changing climate
How well must climate models agree with observations?
No full textThe usefulness of a climate-model simulation cannot be inferred solely from its degree of agreement with observations. Instead, one has to consider additional factors such as internal variability, the tuning of the model, observational uncertainty, the temporal change in dominant processes or the uncertainty in the forcing. In any model-evaluation study, the impact of these limiting factors on the suitability of specific metrics must hence be examined. This can only meaningfully be done relative to a given purpose for using amodel. I here generally discuss these points and substantiate their impact on model evaluation using the example of sea ice. For this example, I find that many standard metrics such as sea-ice area or volume only permit limited inferences about the shortcomings of individual models. © 2015 The Author(s) Published by the Royal Society. All rights reserved
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