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Zabecki , Rommel's insubordination also played a role, leading to a calamitous misuse of resources when Rommel went over the head of his superior, Field Marshal Albert Kesselring , to appeal directly to Hitler to approve an assault on Egypt instead of occupying Malta, as Kesselring and OKW were planning.

Rommel did not follow this principle, which allowed him to achieve some tactical victories, but this contributed to eventual operational and strategic failure in North Africa.

He tolerated this since he had a strong dose of personal ambition and vanity. There are many historical issues surrounding his true merits as a military commander and the extent of his actual involvement in the anti-Hitler conspiracy, and yet on close inspection he comes across as a simple, straightforward man whose talents and character ensured his success in the very particular circumstances that arose throughout his career.

Frankfurter Allgemeine in German. Retrieved 15 June Retrieved 16 March Peter Lang. Great soldiers of world war II.

Archived from the original on 11 December Retrieved 22 September Deutsche Welle. Retrieved 19 October Meeting of Generals. Winfried Heinemann: Wir wollen Bundeswehrsoldaten, die um die moralische Dimension ihres Tuns wissen".

Retrieved 5 June Süddeutsche Zeitung. Archived from the original on 28 August Retrieved 30 June Retrieved 29 October Todestag von Erwin Rommel: Nazi-General oder Widerstandskämpfer?

Retrieved 14 September Der Spiegel. Retrieved 30 May Addington, Larry H. Military Affairs. Atkinson, Rick An Army at Dawn. New York: Picador.

The Guns at Last Light. New York: Henry Holt. Austin, Douglas Malta and British Strategic Policy, — Ball, Simon Alamein: Great Battles.

Oxford University Press. Barnett, Correlli Hitler's Generals. Grove Press. Barr, Niall Beckett ed. Rommel Reconsidered. Mechanicsburg, PA: Stackpole Books.

Battistelli, Pier Paolo Erwin Rommel. Bloomsbury Publishing. Baxter, Ian Afrika Korps. Pen and Sword. Beckett, Ian Beevor, Antony The Second World War.

New York: Back Bay Books. Blumenson, Martin Heroes Never Die: Warriors and Warfare in World War II.

Cooper Square Press. Boog, Horst; Rahn, Werner; Stumpf, Reinhard; Wegner, Bernd Germany and the Second World War: Volume 6: The Global War.

OUP Oxford. Brighton, Terry Masters of Battle: Monty, Patton and Rommel at War. New York: Viking.

Patton, Montgomery, Rommel: Masters of War. Butler, Daniel Allen Field Marshal: The Life and Death of Erwin Rommel.

Caddick-Adams, Peter Monty and Rommel: Parallel Lives. New York, NY: The Overlook Press. Calder, Angus The People's War: Britain — Random House. Ceva, Lucio In John Gooch ed.

Decisive Campaigns of the Second World War. Chambers, Madeline German film seeks to debunk Rommel myth". Retrieved 8 February Citino, Robert Death of the Wehrmacht: The German Campaigns of University Press of Kansas.

Archived from the original on 6 October Retrieved 3 March Coetzee, Daniel Philosophers of War: The Evolution of History's Greatest Military Thinkers.

Connelly, Mark Connelly, Owen On War and Leadership: The Words of Combat Commanders from Frederick the Great to Norman Schwarzkopf. Princeton: Princeton University Press.

Creveld, Martin van Supplying War: Logistics from Wallenstein to Patton. Cambridge: Cambridge University Press. Detsch, Roland Deuel, Wallace R.

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Basic Books. Dowe, Christopher; Hecht, Cornelia David Irving und seine verzerrende Deutungen von Erwin Rommel, Hans Speidel und Cäsar von Hofacker".

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Evans, Richard J. The Third Reich at War. New York: Penguin. Fischer, Thomas Fraser, David Knight's Cross: A Life of Field Marshal Erwin Rommel.

New York: HarperCollins. Retrieved 23 April Friedmann, Jan 23 May Spiegel Online. Retrieved 4 March Gabel, Christopher Great Commanders [Illustrated Edition].

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Amazon Rapids Fun stories for kids on the go. It should be noted that the riverine influence within the coastal zone may be overestimated by our simulations, given the lower-than-observed salinities Fig.

Our results point to an increase in current velocities at the surface under the influence of the flood Fig. Enhancement of the current velocities at the surface, in turn, might have facilitated the spread of the plume towards the outer German Bight in Figs.

Our model-based analysis here is not conclusive but exploratory. Such a mechanistic understanding is essential for policy making, such as the regulation of nutrient-loading rates in rivers see, e.

With a spatial resolution of 1. A potential source of bias in salinity and nutrients along the Elbe plume is the misrepresentation of the Elbe estuary in our model setup Fig.

Other contingent error sources are potential inaccuracies in advective transport rates, e. The structure and process descriptions used for the biogeochemical model introduced in this study are similar to those used recently for studying the interaction between the hydrodynamical and biogeochemical processes in coastal systems, in particular, nutrient cycling and oxygen dynamics, in the North Sea e.

Descriptions of the nonplanktonic components, consisting of two detritus classes; dissolved organic material; dissolved inorganic nutrients; oxygen; and a simple benthic pool to represent benthic remineralization, oxygen consumption and denitrification Fig.

Based on these estimates, within the outer German Bight, we do not expect a large sensitivity of our results to the resolution of benthic processes, but this may be the case for the shallower sites and the Wadden Sea.

Underestimated oxygen depletion Fig. Since the benthic oxygen consumption rates are calculated based on the benthic remineralization rates in our model, the underestimation of benthic oxygen consumption implies an underestimation of the role played by the sediments in nutrient cycling in some locations and at some times of the year.

The response of benthic macrofaunal groups to changes in pelagic productivity Fig. This may imply alterations in the benthic functioning at timescales that may well exceed the scales studied here.

Analyses of such effects with models require a very detailed representation of the benthic communities and their functions.

Such models are rare but see, e. An intermediate step might be to use statistically estimated distributions of benthic organisms for various scenarios e.

In spite of its simplicity, the benthic model is partially successful in estimating the denitrification rates: for the German Bight, the simulated rates reach about 1.

This increase is solely driven by the increased POM loading during the flood Fig. But in reality, the enhanced oxygen depletion in bottom layers Fig.

The sporadic large underestimation errors in P concentrations are identified to occur in some coastal regions during summer months, when the nitrogen concentrations are at their lowest.

Such decoupling of phosphorus and nitrogen in certain Wadden Sea regions is well known and recognized to be driven by the depletion of benthic oxygen during summer, which leads to release of iron-bound P while promoting denitrification in the sediments see, e.

In three out of four stations we considered, chlorophyll concentrations are overestimated Fig. Considering these biases, rather than the absolute values of NPPR estimates, simulated responses to hydrometeorological forcing should be regarded Fig.

Reasons for the overestimation of chlorophyll concentrations seem to be region specific: overestimation of winter concentrations in Terschelling and Noordwijk suggests insufficient respiration rates, whereas spring blooms starting too early at Helgoland suggest inaccuracies in the seasonality of the underwater light climate.

During the summer months, misrepresentation of grazing losses and vertical distribution of chlorophyll e. A detailed identification of the chlorophyll dynamics therefore requires careful consideration of all these factors and comparisons against additional datasets, which is outside of the scope of this study.

However, differences in baseline concentrations at different stations during summer are quite realistically reproduced, suggesting that the large-scale gradients are realistically represented Fig.

Given the limitations of the biogeochemical model discussed above, its predictions should not be interpreted in an absolute sense.

However, the simulated responses by the model are plausible, and therefore the analysis presented in this study is expected to be of heuristic value in gaining a systematic understanding of the role of riverine and meteorological forcing in the shaping of the hydrodynamical and biogeochemical structure of the system.

In this study, we presented a newly developed biogeochemical model and improvements of a hydrodynamical model described in an earlier study.

The coupled hydrodynamical—biogeochemical model system is shown to satisfactorily reproduce the characteristic features of the German Bight ecosystem and the impacts of a year flooding of the Elbe and Weser rivers.

Our results reveal that the flood event coincided with special meteorological conditions in the region, namely a calm and warm summer dominated by an anticyclonic circulation, resulting in particularly intense and widespread stratification.

The stronger stratification and the increased availability of nutrients impacted the primary production in the system and the oxygen levels in the bottom waters.

Through a scenario analysis, we found that the observed anomalies in July were likely driven by the meteorological conditions within the outer German Bight and by the interaction between meteorological and hydrological conditions within the central German Bight, suggesting that the impacts of flood events in the system are context-dependent.

These extreme flooding and meteorological conditions may occur more frequently in the future, which requires a better understanding of the mechanisms governing the response of the coastal systems to such extreme events.

Comparisons of the mixing term strength between model applications then potentially result in differences in the advection scheme performance more than an analysis of the physical effect of mixing mass concentrations would.

There exists a plethora of methods for the specification of horizontal diffusion or isopycnal mixing for ocean models see, e.

The Smagorinsky parameterization achieves such variations by scaling the diffusion coefficient proportionally with the grid size and deformation rates of lateral velocities, e.

Then the horizontal diffusion of tracers, A H , follows:. In Eq. The variant where no diffusion was enabled overestimates the cross-shore salinity gradient along the North Frisian coast, i.

On the other hand, the variant where horizontal diffusion was described with Smagorinsky parameterization has considerably better skill in reproducing the FerryBox measurements along the Büsum—Helgoland ferry track Fig.

In the absence of explicit diffusion, the sum of physical and numerical mixing becomes negative at the mouth of the Elbe and Weser rivers and within their ROFI, implying spuriously enhanced horizontal gradients Fig.

With the application of explicit diffusion, numerical mixing values effectively decrease within both the positive and negative spectra Fig. A2 d , leading to near-complete elimination of negative values in total mixing Fig.

All modeled state variables and fluxes between various pools are shown in Fig. Although this notation is consistent with that used in the Fortran module of abiotic components, the programming notation of the plankton module is somewhat different, due to its different historical origins.

All kinetic rates in planktonic and abiotic components are modified with temperature using the Q 10 rule:. B3, B13 ; limitation of diatoms by Si Eq.

B15 , in phytoplankton Eq. The plankton module provides various options for the representation of nutrient and carbon limitation in a consistent way, which is intended to be further enriched and elaborated in future studies.

Given the suppleness of the model with respect to the description of physiological processes and interactions between plankton groups, the model is provisionally named the Generalized Plankton Model GPM.

Download Print Version Download XLSX. Exudates of the phytoplankton are assumed to be in DOM form Eqs. B2, B Where necessary, multiple values were provided for diatoms and flagellates.

B26, B Zooplankton are assumed to excrete into the DIM pool Eqs. B6, B Here this scheme was extended to multiple nutrients, i.

Where necessary, multiple values were provided for micro- and mesozooplankton. The abiotic components describe the geochemical transformation between various organic and inorganic pools DIM, DOM, small and large detritus classes, O 2 , and the particulate organic matter in the benthos — B-POM; see Fig.

The latter is described here as a first-order kinetic reaction Eq. B43 , instead of with a more detailed description of scavenging of DOM by bacterial biomass in the original model.

Coupling of the abiotic component with the planktonic components is mediated through the uptake of DIM by phytoplankton Eqs.

B3, B4 , and the recycling of the dead and surplus material. The unassimilated fraction of the ingestion by zooplankton is distributed into the DOM Eq.

B18, B25 is distributed into the small and large detritus classes Eqs. B36, B For Si, there are no DOM or det S Si pools Fig.

In the GETM, light intensity at a given depth, I z , is described by. For describing the contribution of SPM, K SPM , which is not explicitly modeled here, we use an analytical function of the form:.

OK designed the study with contributions from YGV, developed the biogeochemical model, performed the model skill assessment and conducted the model-based analyses with contributions from FC, and prepared the first draft of the manuscript.

JEEvB provided the monthly average nutrient concentrations, and YGV assisted in the compilation of the monitoring data.

RH and KK assisted in the improvement of the hydrodynamical model with horizontal diffusion. All co-authors contributed to the discussion of the results and revisions of the manuscript.

Data at Helgoland were provided by the Alfred Wegener Institute AWI and at Norderelbe, Suederpiep and Westerhever were provided by the Landesamt für Landwirtschaft, Umwelt und ländliche Räume des Landes Schleswig-Holstein.

Noordwijk and Terschelling data were provided by the Rijkswaterstaat. Simulations were performed on the Mistral supercomputer of the German Climate Computing Center DKRZ.

We thank Hermann-J. This research has been supported by the Umweltbundesamt grant no. The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association.

Ahmerkamp, S. Amann, T. Shelf S. Androsov, A. Model Dev. Backhaus, J. Baird, M. Baretta, J. Sea Res. Barthel, K. Becker, E.

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