Analysis of the Global Spectrum of the Atmospheric Horizontal Kinetic Energy from the Boundary Layer to the Mesopause

This thesis contributes to the discussion, how the large-scale and mesoscale atmospheric motions interact and how the vertical coupling of the atmosphere is influenced by mesoscale waves. The results from our mechanistic GCM are twofold. Firstly, the mesoscale upper tropospheric kinetic energy spectrum can be explained by stratified turbulence. Secondly, the mesoscale energy deposition in the upper mesosphere can be explained by the vertical pressure flux carried by mesoscale gravity waves from the troposphere, which is converted into kinetic energy of these waves and then dissipated

Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods

Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system “Mittelfristige Klimaprognose” (MiKlip). Among the tested methods, three tackle aspects of model‐consistent initialization using the ensemble Kalman filter, the filtered anomaly initialization, and the initialization method by partially coupled spin‐up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter corrects each ensemble member with the ensemble mean during model integration. And the bred vectors perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low‐resolution configuration (Preop‐LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization. Results show that the tested methods provide an added value for the prediction skill as compared to Preop‐LR in that they improve prediction skill over the eastern and central Pacific and different regions in the North Atlantic Ocean. In this respect, the ensemble Kalman filter and filtered anomaly initialization show the most distinct improvements over Preop‐LR for surface temperatures and upper ocean heat content, followed by the bred vectors, the ensemble dispersion filter, and MODINI. However, no single method exists that is superior to the others with respect to all metrics considered. In particular, all methods affect the Atlantic Meridional Overturning Circulation in different ways, both with respect to the basin‐wide long‐term mean and variability and with respect to the temporal evolution at the 26° N latitude

Skillful decadal prediction of German Bight storm activity

We evaluate the prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcast system for German Bight storm activity (GBSA) on a multiannual to decadal scale. We define GBSA every year via the most extreme 3-hourly geostrophic wind speeds, which are derived from mean sea-level pressure (MSLP) data. Our 64-member ensemble of annually initialized hindcast simulations spans the time period 1960–2018. For this period, we compare deterministically and probabilistically predicted winter MSLP anomalies and annual GBSA with a lead time of up to 10 years against observations. The model produces poor deterministic predictions of GBSA and winter MSLP anomalies for individual years but fair predictions for longer averaging periods. A similar but smaller skill difference between short and long averaging periods also emerges for probabilistic predictions of high storm activity. At long averaging periods (longer than 5 years), the model is more skillful than persistence- and climatology-based predictions. For short aggregation periods (4 years and less), probabilistic predictions are more skillful than persistence but insignificantly differ from climatological predictions. We therefore conclude that, for the German Bight, probabilistic decadal predictions (based on a large ensemble) of high storm activity are skillful for averaging periods longer than 5 years. Notably, a differentiation between low, moderate, and high storm activity is necessary to expose this skill

An 1888 Volcanic Collapse Becomes a Benchmark for Tsunami Models

When volcanic mountains slide into the sea, they trigger tsunamis. How big are these waves, and how far away can they do damage? Ritter Island provides some answers

Skilful prediction of cod stocks in the North and Barents Sea a decade in advance

Reliable information about the future state of the ocean and fish stocks is necessary for informed decision-making by fisheries scientists, managers and the industry. However, decadal regional ocean climate and fish stock predictions have until now had low forecast skill. Here, we provide skilful forecasts of the biomass of cod stocks in the North and Barents Seas a decade in advance. We develop a unified dynamical-statistical prediction system wherein statistical models link future stock biomass to dynamical predictions of sea surface temperature, while also considering different fishing mortalities. Our retrospective forecasts provide estimates of past performance of our models and they suggest differences in the source of prediction skill between the two cod stocks. We forecast the continuation of unfavorable oceanic conditions for the North Sea cod in the coming decade, which would inhibit its recovery at present fishing levels, and a decrease in Northeast Arctic cod stock compared to the recent high levels. North Sea cod stock may not recover in the decade 2020-2030 while Northeast Arctic cod biomass is also predicted to decline but will be better able to recover, according to an integration of statistical fisheries models and climate predictionspublishedVersio

Seasonal Prediction of Arabian Sea Marine Heatwaves

Marine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (Sardinella longiceps)

Can environmental conditions at North Atlantic deep-sea habitats be predicted several years ahead? - Taking sponge habitats as an example

Predicting the ambient environmental conditions in the coming several years to one decade is of key relevance for elucidating how deep-sea habitats, like for example sponge habitats, in the North Atlantic will evolve under near-future climate change. However, it is still not well known to what extent the deep-sea environmental properties can be predicted in advance. A regional downscaling prediction system is developed to assess the potential predictability of the North Atlantic deep-sea environmental factors. The large-scale climate variability predicted with the coupled Max Planck Institute Earth System Model with low-resolution configuration (MPI-ESM-LR) is dynamically downscaled to the North Atlantic by providing surface and lateral boundary conditions to the regional coupled physical-ecosystem model HYCOM-ECOSMO. Model results of two physical fields (temperature and salinity) and two biogeochemical fields (concentrations of silicate and oxygen) over 21 sponge habitats are taken as an example to assess the ability of the downscaling system to predict the interannual to decadal variations of the environmental properties based on ensembles of retrospective predictions over the period from 1985 to 2014. The ensemble simulations reveal skillful predictions of the environmental conditions several years in advance with distinct regional differences. In areas closely tied to large-scale climate variability and ice dynamics, both the physical and biogeochemical fields can be skillfully predicted more than 4 years ahead, while in areas under strong influence of upper oceans or open boundaries, the predictive skill for both fields is limited to a maximum of 2 years. The simulations suggest higher predictability for the biogeochemical fields than for the physical fields, which can be partly attributed to the longer persistence of the former fields. Predictability is improved by initialization in areas away from the influence of Mediterranean outflow and areas with weak coupling between the upper and deep oceans. Our study highlights the ability of the downscaling regional system to predict the environmental variations at deep-sea benthic habitats on time scales of management relevance. The downscaling system therefore will be an important part of an integrated approach towards the preservation and sustainable exploitation of the North Atlantic benthic habitats

Forecast-Oriented Assessment of Decadal Hindcast Skill for North Atlantic SST

We demonstrate in this paper that conventional time-averaged decadal hindcast skill estimates can overestimate or underestimate the credibility of an individual decadal climate forecast.We show that hindcast skill in a long period can be higher or lower than skill in its subperiods. Instead of using time-averaged hindcast skill measures, we propose to use the physical state of the climate system at the beginning of the forecast to judge its credibility.We analyze hindcasts of North Atlantic sea surface temperature (SST) in an initialized prediction system based on the MPI-ESM-LR for the period 1901–2010. Subpolar North Atlantic Ocean heat transport (OHT) strength at hindcast initialization largely determines the skill of these hindcasts:We find high skill after anomalously strong or weak OHT, but low skill after average OHT. This knowledge can be used to constrain conventional hindcast skill estimates to improve the assessment of credibility for a decadal forecast

From gradual spreading to catastrophic collapse - Reconstruction of the 1888 Ritter Island volcanic sector collapse from high-resolution 3D seismic data

Volcanic island flank collapses have the potential to trigger devastating tsunamis threatening coastal communities and infrastructure. The 1888 sector collapse of Ritter Island, Papua New Guinea (in the following called Ritter) is the most voluminous volcanic island flank collapse in historic times. The associated tsunami had run-up heights of more than 20 m on the neighboring islands and reached settlements 600 km away from its source. This event provides an opportunity to advance our understanding of volcanic landslide-tsunami hazards. Here, we present a detailed reconstruction of the 1888 Ritter sector collapse based on high-resolution 2D and 3D seismic and bathymetric data covering the failed volcanic edifice and the associated mass-movement deposits. The 3D seismic data reveal that the catastrophic collapse of Ritter occurred in two phases: (1) Ritter was first affected by deep-seated, gradual spreading over a long time period, which is manifest in pronounced compressional deformation within the volcanic edifice and the adjacent seafloor sediments. A scoria cone at the foot of Ritter acted as a buttress, influencing the displacement and deformation of the western flank of the volcano and causing shearing within the volcanic edifice. (2) During the final, catastrophic phase of the collapse, about 2.4 km³ of Ritter disintegrated almost entirely and travelled as a highly energetic mass flow, which incised the underlying sediment. The irregular topography west of Ritter is a product of both compressional deformation and erosion. A crater-like depression underlying the recent volcanic cone and eyewitness accounts suggest that an explosion may have accompanied the catastrophic collapse. Our findings demonstrate that volcanic sector collapses may transform from slow gravitational deformation to catastrophic collapse. Understanding the processes involved in such a transformation is crucial for assessing the hazard potential of other volcanoes with slowly deforming flanks such as Mt. Etna or Kilauea