TEC measurements and modelling over Southern Africa during magnetic storms; a comparative analysis

This paper presents the results from a study designed to investigate the ability of a newly developed neural network (NN) based model to follow total electron content (TEC) dynamics over the Southern African region. The investigation is carried out by comparing results from the NN model with actual TEC data derived from Global Positioning System (GPS) observations and TEC values predicted by the International Reference Ionosphere (IRI-2007) model during magnetic storm periods over Southern Africa. The magnetic storm conditions chosen for the study presented in this paper occurred during the periods 16–21 April 2002, 1–6 October 2002, and 28 October–01 November 2003. A total of six South African GPS stations were used for the validation of the two models during these periods. A statistical analysis of the comparison between the actual TEC behaviour and that predicted by the two models is shown. In addition, ionosonde measurements from the South African Louisvale (28.5°S, 21.2°E) station, located close to one of the validation GPS stations used, are also considered during the Halloween storm period of 28–31 October 2003. The generalisation of TEC behaviour by the NN model is demonstrated by producing predicted TEC maps during magnetic storm periods over South Africa. Presented results demonstrate the ability of NNs in predicting TEC variability over South Africa during magnetically disturbed conditions, and highlight areas for improvement.     

Real-time multi-model decadal climate predictions

We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.     

Impact of Climate Change on Agricultural Production in the Sahel – Part 1. Methodological Approach and Case Study for Millet in Niger

In the last 30 years the climate of the West African Sahel has shown various changes, especially in terms of rainfall, of which inter-annual variabilityis very high. This has significant consequences for the poor-resource farmers, whose incomes depend mainly on rainfed agriculture. The West African Sahel is already known as an area characterized by important interaction between climate variability and key socio-economic sectors such as agriculture and water resources. More than 80% of the 55 million population of West African Sahel is rural, involved in agriculture and stock-farming, the two sectors contributing almost 35% of the countries' GDPs. It is thereforeobvious that climate change seriously affects the economies of these countries. Adding to this situation the high rate of population increase(3%), leading to progressive pressure upon ecosystems, and poorsanitary facilities, one comes to the conclusion that Sahelian countries, Niger amongst them, will be highly vulnerable to climate change.This paper investigates the impact of current climate variability and future climate change on millet production for three major millet-producing regions in Niger. Statistical models have been used to predict the effects of climate change on future production on the basis of thirteen available predictors. Based on the analysis of the past 30-years of rainfall and production data, the most significant predictors of the model are (i) seasurface temperature anomalies, (ii) the amount of rainfall in July, August and September, (iii) the number of rainy days and (iv) the wind erosion factor. In 2025, production of millet is estimated to be about 13% lower as a consequence of climate change, translated into a reduction of the total amount of rainfall for July, August and September, combined with an increase in temperature while maintaining other significant predictors at a constant level. Subsequently,various potential strategies to compensate this loss are evaluated, including those to increase water use efficiency and to cultivate varieties that are adapted to such circumstances.     

Scientific uncertainty and climate change: Part II. Uncertainty and mitigation

In public debate surrounding climate change, scientific uncertainty is often cited in connection with arguments against mitigative action. This article examines the role of uncertainty about future climate change in determining the likely success or failure of mitigative action. We show by Monte Carlo simulation that greater uncertainty translates into a greater likelihood that mitigation efforts will fail to limit global warming to a target (e.g., 2 °C). The effect of uncertainty can be reduced by limiting greenhouse gas emissions. Taken together with the fact that greater uncertainty also increases the potential damages arising from unabated emissions (Lewandowsky et al. 2014), any appeal to uncertainty implies a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.     

Fine-Scale Characteristics of Temperature, Wind, and Turbulence in the Lower Atmosphere (0–1,300 m) Over the South Peruvian Coast

We report results of preliminary high-resolution in situ atmospheric measurements through the boundary layer and lower atmosphere over the southern coast of Perú. This region of the coast is of particular interest because it lies adjacent to the northern coastal edge of the sub-tropical south-eastern Pacific, a very large area of ocean having a persistent stratus deck located just below the marine boundary layer (MBL) inversion. Typically, the boundary layer in this region during winter is topped by a quasi-permanent, well-defined, and very large temperature gradient. The data presented herein examine fine-scale details of the coastal atmosphere at a point where the edge of this MBL extends over the coastline as a result of persistent onshore flow. Atmospheric data were gathered using a recently-developed in-house constructed, GPS-controlled, micro-autonomous-vehicle aircraft (the DataHawk). Measured quantities include high-resolution profiles of temperature, wind, and turbulence structure from the surface to 1,300 m.     

Studies of the formation process of water-in-oil emulsions

This paper summarizes studies to determine the formation process of water-in-oil emulsions and the stability of such emulsions formed in the laboratory and in a large test tank. These studies have confirmed that water-in-oil mixtures can be grouped into four states: stable emulsions, unstable water-in-oil mixtures, mesostable emulsions, and entrained water. These states are differentiated by rheological properties as well as by differences in visual appearance. The viscosity of a stable emulsion at a shear rate of one reciprocal second is about three orders of magnitude greater than that of the starting oil. An unstable emulsion usually has a viscosity no more than about 20 times greater than that of the starting oil. A stable emulsion has a significant elasticity, whereas an unstable emulsion does not. A mesostable emulsion has properties between stable and unstable, but breaks down within a few days of standing. The usual situation is that emulsions are either obviously stable, mesostable, or unstable. Entrained water, water suspended in oil by viscous forces alone, is also evident. Very few emulsions have questionable stability. Analytical techniques were developed to test these observations.

The type of emulsion produced is determined primarily by the properties of the starting oil. The most important of these properties are the asphaltene and resin content and the viscosity of the oil. The composition and property ranges of the starting oil that would be required to form each of the water-in-oil states are discussed in this paper.     

Selection of the wavenumbers k using an optimization method for the inverse Fourier transform in 2.5D electrical modelling

An optimization method is used to select the wavenumbers k for the inverse Fourier transform in 2.5D electrical modelling. The model tests show that with the wavenumbers k selected in this way the inverse Fourier transform performs with satisfactory accuracy.     

Geodynamic Evolution of Northeastern Tunisia During the Maastrichtian–Paleocene Time: Insights from Integrated Seismic Stratigraphic Analysis

The Maastrichtian–Paleocene El Haria formation was studied and defined in Tunisia on the basis of outcrops and borehole data; few studies were interested in its three-dimensional extent. In this paper, the El Haria formation is reviewed in the context of a tectono-stratigraphic interval using an integrated seismic stratigraphic analysis based on borehole lithology logs, electrical well logging, well shots, vertical seismic profiles and post-stack surface data. Seismic analysis benefits from appropriate calibration with borehole data, conventional interpretation, velocity mapping, seismic attributes and post-stack model-based inversion. The applied methodology proved to be powerful for charactering the marly Maastrichtian–Paleocene interval of the El Haria formation. Migrated seismic sections together with borehole measurements are used to detail the three-dimensional changes in thickness, facies and depositional environment in the Cap Bon and Gulf of Hammamet regions during the Maastrichtian–Paleocene time. Furthermore, dating based on their microfossil content divulges local and multiple internal hiatuses within the El Haria formation which are related to the geodynamic evolution of the depositional floor since the Campanian stage. Interpreted seismic sections display concordance, unconformities, pinchouts, sedimentary gaps, incised valleys and syn-sedimentary normal faulting. Based on the seismic reflection geometry and terminations, seven sequences are delineated. These sequences are related to base-level changes as the combination of depositional floor paleo-topography, tectonic forces, subsidence and the developed accommodation space. These factors controlled the occurrence of the various parts of the Maastrichtian–Paleocene interval. Detailed examinations of these deposits together with the analysis of the structural deformation at different time periods allowed us to obtain a better understanding of the sediment architecture in depth and the delineation of the geodynamic evolution of the region.