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

Der Wavelet-basierte Organisationsindex als Maß der konvektiven Organisation über Deutschland und dem tropischen Atlantik

In dieser Arbeit wird die konvektive Organisation mithilfe von zweidimensionalen Wavelet-Transformationen der Regenrate und der Helligkeitstemperatur analysiert. Aus dem Wavelet-Spektrum lassen sich Informationen über die Skala der Konvektion, deren Intensität und deren Orientierung ableiten. Jede der drei Größen bildet eine Komponente des neu eingeführten Wavelet-basierten Organisationsindex (WOI). In einer ersten Studie wird der WOI benutzt, um zwischen sehr unorganisierter Konvektion und organisierten konvektiven Strukturen (Multizellen, Squall-Line) zu unterscheiden. Grundlage dafür bilden drei Fallstudien mit hochauflösenden ICON-Simulationen über Deutschland. Die berechneten Wavelet-Spektren der Regenraten zeigen, dass unorganisierte Konvektion kleinskaliger ist und eine geringere Intensität aufweist als organisierte Konvektion in Form von Multizellen und Squall-Lines. Letztere zeichnen sich zusätzlich durch eine Richtungsabhängigkeit im Wavelet-Spektrum aus. Ein Vergleich mit Wavelet-Spektren aus Radarbeobachtungen liefern ein ähnliches Bild. Die dynamischen und konvektiven Variablen wie Windscherung, Helizität, CIN und CAPE aus dem ICON-Modell offenbaren derweil zwei unterschiedliche Cluster: Wenig organisierte Konvektion tritt in Verbindung mit schwachen Höhenwinden und einer damit einhergehenden geringen vertikalen Windscherung auf, während sich die organisierte Konvektion durch ein stärkeres Forcing entwickeln kann. Vor Ausbruch der organisierten Konvektion kann sich im Tagesverlauf mehr CAPE aufbauen, da die Luftmasse durch erhöhtes CIN anfangs gedeckelt ist. Neben WOI werden auch drei in der Literatur etablierte konvektive Organisationsindexe berechnet. Es stellt sich heraus, dass WOI in dieser Fallstudie unorganisierte Konvektion von organisierten Strukturen unterscheiden kann, während die anderen Indexe nur 90 % aller Zeitschritte richtig zuordnen können. Die drei WOI-Komponenten sind untereinander nicht direkt vergleichbar, sodass im nächsten Schritt eine Normierung eingeführt wird. Weiterhin stellt sich heraus, dass durch die Wahl eines alternativen Wavelets die Struktur des Niederschlags besser erfasst werden kann. Durch diese Anpassungen wird es möglich, die konvektive Organisation erstmals auf einer Karte zu lokalisieren (LWOI) und somit Regionen unterschiedlicher konvektiver Organisation zu identifizieren. Diese Erweiterung von WOI in zwei Dimensionen wird auf ICON-Simulationen über dem tropischen Atlantik angewendet. Im Vergleich zu den maritimen konvektiven Umlagerungen ist die Konvektion über dem afrikanischen Festland großskaliger und intensiver. Ähnliche Erkenntnisse liefert LWOI für Niederschlagsabschätzungen via Satelliten im Mikrowellen- und Infrarotbereich. Ein Vergleich mit den dynamischen und konvektiven Variablen zeigt auch hier klare Unterschiede zwischen den unterschiedlichen Graden der konvektiven Organisation über dem Festland und dem benachbarten Atlantik. Im dritten Schritt wird die Struktur von Schauern und Gewittern sowie bei Hagelereignissen oder Starkniederschlägen mit dem finalen Index LW untersucht. Eine abschließende Optimierung sorgt dafür, dass der LW frei von Schwellenwerten ist und auf einer beliebigen zweidimensionalen Variable flexibel anwendbar ist. Während zuvor Regenraten als Grundlage für das Wavelet-Spektrum dienten, wird der Index LW auch auf Helligkeitstemperaturen angewendet. Es zeigt sich, dass Hagel- und Starkregenereignisse mit intensiven Niederschlägen und niedrigen Helligkeitstemperaturen einhergehen. Die Skala der intensiven Konvektion ist dabei sehr klein, d. h., dass das Ereignis auf einen sehr engen Raum begrenzt ist. Darüber hinaus ist es sogar möglich, mithilfe von LW zwischen Schauern, Gewittern und Hagel-/Starkregenereignissen zu klassifizieren.The wavelet-based organization index as a measure of convective organization over Germany and the tropical Atlantic Convective organization is analyzed with help of a two-dimensional wavelet transform of rain rate and brightness temperature. From the wavelet spectrum, information about the scale of convection, its intensity and its orientation can be derived. Each of the three quantities forms a component of the so-called wavelet-based organization index (WOI). First, WOI is used to distinguish between scattered convection and a linearly organized squall line in the midlatitudes. A comparison with dynamic and convective variables within three case studies shows that WOI differentiates better between unorganized structures and linear convection than ordinary organization indices from literature. However, the original definition of WOI still has some weaknesses. Through normalization and the choice of a different wavelet, all three components become more comparable. Thus, convective organization can be localized on a map for the first time (LWOI). It turns out that the organization of squall lines over Africa differs from the maritime convection over the tropical Atlantic in scale and intensity. A comparison with the dynamic and convective variables also shows clear differences between the different degrees of convective organization. In the third and final step, the structure of showers and thunderstorms as well as in the area of hail or heavy precipitation is examined with the final index LW. A final optimization ensures that LW is also free of threshold values and can be flexibly applied to any two-dimensional variable. The index LW is also applied to brightness temperatures instead of rain rates. It turns out that hail and heavy rain events are associated with intense rainfall and low brightness temperatures. The scale of the intense convection is very small, i.e. the events local phenomena. Furthermore, it is even possible to classify between showers, thunderstorms and hail/heavy rain events using LW

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