ALBERT

Description: We apply a coupled modelling system composed of a state-of-the-art hydrodynamical model and a low complexity biogeochemical model to an idealized Iberian Peninsula upwelling system to identify the main drivers of dissolved oxygen variability and to study its response to changes in the duration of the upwelling season and in phytoplankton growth regime. We find that the export of oxygenated waters by upwelling front turbulence is a major sink for nearshore dissolved oxygen. In our simulations of summer upwelling, when phytoplankton population is generally dominated by diatoms whose growth is largely enhanced by nutrient input, net primary production and air-sea exchange compensate dissolved oxygen depletion by offshore export over the shelf. A shorter upwelling duration causes relaxation of upwelling winds and a decrease in offshore export, resulting in a slight increase of net dissolved oxygen enrichment in the coastal region as compared to longer upwelling durations. When phytoplankton is dominated by groups less sensitive to nutrient inputs, growth rates decrease and the coastal region becomes net heterotrophic. Together with the physical sink, this lowers the net oxygenation rate of coastal waters, that remains positive only because of air-sea exchanges. These findings help disentangling the physical and biogeochemical controls of dissolved oxygen in upwelling systems and, together with projections of increased duration of upwelling seasons and phytoplankton community changes, suggest that the Iberian coastal upwelling region may become more vulnerable to hypoxia and deoxygenation.

Description: The description of the relationship between interplanetary plasma and geomagnetic activity requires complex models. Drastically reducing the ambition of describing this detailed complex interaction, and if we are interested only in the fractality properties of the time-series of its characteristic parameters, a magnetohydrodynamic (MHD) shell model forced using solar wind data, might provide a possible novel approach. In this paper we study the relation between the activity of the magnetic energy dissipation rate obtained in one such model, which may describe geomagnetic activity, and the fractal dimension of the forcing. In different shell model simulations, the forcing is provided by the solution of a Langevin equation where a white noise is implemented. Since this forcing has shown its unsuitableness in describing the driver due to solar wind action, we propose to consider the fluctuations of the product between the velocity and the magnetic field solar wind data as the noise in Langevin equation, whose solution provides the forcing in the magnetic field equation. We compare the fractal dimension of the magnetic energy dissipation rate obtained, of the magnetic forcing term, and of the fluctuations of v · bz, with the activity of the magnetic energy dissipation rate. We examine the dependence of these fractal dimensions on the solar cycle. We show that all measures of activity have a peak near solar maximum. Moreover, both the fractal dimension computed for the fluctuations of v · bz time series and the fractal dimension of the magnetic forcing have a minimum near solar maximum. This suggests that the complexity of the noise term in the Langevin equation may have a strong effect in the activity of the magnetic energy dissipation rate.

Description: Seasonal predictions from climate models are increasingly invoked in various sectors like water management, energy and transport to cite a few. This study investigates the post-processing of the seasonal predictions of the EUROSIP multi-model system. The hindcasts comprise samples of 23 to 36 years and ensembles of 10 to 28 members depending on the 5 models included. Skill scores both deterministic and probabilistic are calculated in order to compare the impact of the post-processing and help selecting – if any – the multi- or single-model and the post-processing method best suited for a specific location, target season and lead-time. The presence of trends and the cross-validation setting add some complexity to the already heterogeneous database. This study focuses on six cases in Western Europe and the Mediterranean Region. The forecasts of three monthly averages of surface temperature and of sea mean sea level pressure are compared with the corresponding ERA Interim reanalysis data whereas the forecasts of precipitation are evaluated with the rain-gauge data from the Global Precipitation Climatology Centre. The skills of seasonal predictions in the extra-tropics are limited and our results are no exception. There is a significant skill for the spring temperature forecast with model initiation in March for all but one case studies and the skill is extending to the initiation begin of February for Belgium. There is is also a significant skill for the summer temperature for the case studies in the Mediterranean region. For these area, the skill comes in large part from the global warming so that after having de-trended the data, a null improvement cannot be excluded. Autumn temperature in UK and in the Turkey is forecast with some skill as well as winter temperature in UK and Greece. Precipitation is even more difficult to forecast: the two spots where skill scores are significantly positive are Sweden and Greece during winter with initialisation on the first December. It has been shown that multi-model ensemble improve the skills in many cases and that taking into account the longest common period of hindcasts results in better and less uncertain skill scores. For all these cases, the post-processing method and the model or model combination resulting in the best skill score have been selected.

Description: We survey temperature patterns and heat transport in convective boundary layers (CBLs) from the perspective that these are emergent properties of far-from-equilibrium, complex dynamical systems. We use the term 'plumes' to denote the temperature patterns, in much the same way that the term 'eddies' is used to describe patterns of motion in turbulent flows. We introduce a two-temperature (2T) toy model to connect the scaling properties of temperature gradients, temperature variance and heat transport to the geometric properties of plumes. We then examine temperature (T) probability density functions and w-T joint probability density functions, T spectra and wT cospectra observed both within and above the surface friction layer. Here w is vertical velocity. We interpret these in terms of the properties of the plumes that give rise to them. We focus first on the self-similarity property of the plumes above the SFL, and then introduce new scaling results from within the SFL, which show that T spectra and wT cospectra are not self-similar with height at small heights z/zs 

Description: Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has been shown to provide valuable information on past climate variability. In turn, it has also been found that the robustness of the obtained results differs among proxies from different palaeoclimate archives. To systematically test the suitability of wRNA for studying different types of palaeoclimate proxy time series, we use the framework of forward proxy modelling. For this, we create artificial input time series with different properties and, in a first step, compare the time series properties of the input and the model output time series. In a second step, we compare the areawise significant anomalies detected using wRNA. For proxies from tree and lake archives, we find that significant anomalies present in the input time series are sometimes missed in the input time series after the nonlinear filtering by the corresponding models. For proxies from speleothems, we observe falsely identified significant anomalies that are not present in the input time series. Finally, for proxies from ice cores, the wRNA results show the best correspondence with those for the input data. Our results contribute to improve the interpretation of windowed recurrence network analysis results obtained from real-world palaeoclimate time series.

Description: Towards the end of the last century, B. Mandelbrot saw the importance, revealed the beauty, and robustly promoted (multi)fractals. Multiplicative cascades are closely related and provide simple models for the study of turbulence and chaos. For pedagogical reasons, but also due to technical difficulties, continuous stochastic models have been favoured over discrete cascades. Particularly important are the α, the β and the p model (Lovejoy and Scherzter 2013, Chapter 3; de Wijs (1951, 1953). It is the aim of this contribution to introduce original concepts that shed new light on the latter paradigmatic cascade and allow key features to be derived in a rather elementary fashion. To this end, we introduce and study a discrete version of the p model which is based on a new kind of sampling. Technical machinery can be kept simple, therefore formulas are explicit, proofs extend standard arguments, and potential extensions are numerous. Thus the proposed line of investigation may enrich and simplify received multifractal analyses.

Description: We consider the statistical properties of solutions of the stochastic fractional relaxation equation that has been proposed as a model for the earth's energy balance. In this equation, the (scaling) fractional derivative term models energy storage processes that occur over a wide range of space and time scales. Up until now, stochastic fractional relaxation processes have only been considered with Riemann-Liouville fractional derivatives in the context of random walk processes where it yields highly nonstationary behaviour. For our purposes we require the stationary processes that are the solutions of the Weyl fractional relaxation equations whose domain is −∞ to t rather than 0 to t. We develop a framework for handling fractional equations driven by white noise forcings. To avoid divergences, we follow the approach used in fractional Brownian motion (fBm). The resulting fractional relaxation motions (fRm) and fractional relaxation noises (fRn) generalize the more familiar fBm and fGn (fractional Gaussian noise). We analytically determine both the small and large scale limits and show extensive analytic and numerical results on the autocorrelation functions, Haar fluctuations and spectra. We display sample realizations. Finally, we discuss the prediction of fRn, fRm which – due to long memories is a past value problem, not an initial value problem. We develop an analytic formula for the fRn forecast skill and compare it to fGn. Although the large scale limit is an (unpredictable) white noise that is attained in a slow power law manner, when the temporal resolution of the series is small compared to the relaxation time, fRn can mimick a long memory process with a wide range of exponents ranging from fGn to fBm and beyond. We discuss the implications for monthly, seasonal, annual forecasts of the earth's temperature.

Description: Geomagnetic storms are caused by solar wind southward magnetic fields that impinge upon the Earth’s magnetosphere (Dungey, 1961). How can we forecast the occurrence of these interplanetary events? We view this as the most important challenge in Space Weather. We discuss the case for magnetic clouds (MCs), interplanetary sheaths upstream of ICMEs, corotating interaction regions (CIRs) and high speed streams (HSSs). The sheath- and CIR-related magnetic storms will be difficult to predict and will require better knowledge of the slow solar wind and modeling to solve. There are challenges for forecasting the fluences and spectra of solar energetic particles. This will require better knowledge of interplanetary shock properties from the Sun to 1 AU (and beyond), the upstream slow solar wind and energetic seed particles. Dayside aurora, triggering of nightside substorms, and formation of new radiation belts can all be caused by shock and interplanetary ram pressure impingements onto the Earth’s magnetosphere. The acceleration and loss of relativistic magnetospheric killer electrons and penetrating electric fields in terms of causing positive and negative ionospheric storms are currently reasonable well understood, but refinements can still be made. The forecasting of extreme events (extreme shocks, extreme solar energetic particle events, and extreme geomagnetic storms (Carrington events or greater)) are also discussed. Energetic particle precipitation and ozone destruction is briefly discussed. For many of the studies, the Parker Solar Probe, Solar Orbiter, Magnetospheric Multiscale Mission (MMS), Arase, and SWARM data will be useful.

Description: The dynamics of three local models, for momentum transfer at the air-sea interface, is compared. The models differ by whether or not the ocean velocity is included in the shear calculation applied to the ocean and the atmosphere. All three cases are employed in climate or ocean simulations. Analytic calculations for the models with deterministic and random forcing (white and coloured) are presented. The short term behaviour is similar in all models, which only small quantitative differences, while the long-term behaviour differs qualitatively between the models. The fluctuation-dissipation-relation, which connects the fast atmospheric motion to the slow oceanic dynamics, is established for all models with random forcing. The fluctuation-dissipation-theorem, which compares the response to an external forcing to internal fluctuations is established for a white-noise forcing and a coloured forcing when the phase space is augmented by the forcing variable. Using results from numerical integrations of stochastic differential equations it is shown that the fluctuation-theorem, which compares the probability of positive to negative fluxes of the same magnitude, averaged over time-intervals of varying length, holds for the energy gained by the ocean from the atmosphere.

Description: In the recent years there are several reporting’s of anomalous seismic induced temporal changes in soil radon emanation. It is however well known that radon anomalies apart from seismic activity are also governed and controlled by meteorological parameters. This is the major complication which arise for isolating the seismic induced precursory signals. Here in the investigation the soil radon emanations temporal variability at MPGO, Tezpur, is scrutinized in the lime light of singular spectrum analysis (SSA). Further prior applying SSA Digital filter (Butterworth low pass) is applied to remove the high frequency quasi periodic component in the time series of soil radon emanation. It was scrutinized that sum of just 9 eigenfunctions were sufficient enough for reproducing the prominent characteristics of the overall variation. This perhaps also evinces that more significantly produced fluctuations are mostly free from natural variations. The variations in soil temperature was observed to be dominated by daily variations similar to radon variation which account to 97.99 % whereas soil pressure accounts for 100 % of the total variance which suggests that daily variations of soil radon (Rn-222) emanation are controlled by soil pressure in MPGO, Tezpur during the investigation period followed by soil temperature. The study concludes that SSA eliminates diurnal and semidiurnal components from time series of soil radon emanation for better correlation of soil radon emanation with earthquakes.