The Anomalous Merging of the African and North Atlantic Jet Streams during the Northern Hemisphere Winter of 2010

The North Atlantic jet stream during winter 2010 was unusually zonal, so the typically separated Atlantic and African jets were merged into one zonal jet. Moreover, the latitude–height structure and temporal variability of the North Atlantic jet during this winter were more characteristic of the North Pacific. This work examines the possibility of a flow regime change from an eddy-driven to a mixed eddy–thermally driven jet. A monthly jet zonality index is defined, which shows that a persistent merged jet state has occurred in the past, both at the end of the 1960s and during a few sporadic months. The anomalously zonal jet is found to be associated with anomalous tropical Pacific diabatic heating and eddy anomalies similar to those found during a negative North Atlantic Oscillation (NAO) state. A Lagrangian back-trajectory diagnosis of eight winters suggests the tropical Pacific is a source of momentum to the Atlantic and African jets and that this source was stronger during the winter of 2010. The results suggest that the combination of weak eddy variance and fluxes in the North Atlantic, along with strong tropical heating, act to push the jet toward a merged eddy–thermally driven state. The authors also find significant SST anomalies in the North Atlantic, which reinforce the anomalous zonal winds, particularly in the eastern Atlantic.

Terrestrial Radar Interferometric Measurement of Hillslope Deformation and Atmospheric Disturbances in the Illgraben Debris-Flow Catchment, Switzerland

We describe a method for rapid identification and precise quantification of slope deformation using a portable radar interferometer. A rockslide with creep-like behavior was identified in the rugged and inaccessible headwaters of the Illgraben debris-flow catchment, located in the Central Swiss Alps. The estimated volume of the moving rock mass was approximately 0.5 x 10(6) m(3) with a maximum daily (3-D) displacement rate of 3 mm. Fast scene acquisition in the order of 6 s/scene led to uniquely precise mapping of spatial and temporal variability of atmospheric phase delay. Observations led to a simple qualitative model for prediction of atmospheric disturbances using a simple model for solar radiation, which can be used for advanced campaign planning for short observation periods (hours to days).

Establishing the skill of climate field reconstruction techniques for precipitation with pseudoproxy experiments

This study aims at assessing the skill of several climate field reconstruction techniques (CFR) to reconstruct past precipitation over continental Europe and the Mediterranean at seasonal time scales over the last two millennia from proxy records. A number of pseudoproxy experiments are performed within the virtual reality ofa regional paleoclimate simulation at 45 km resolution to analyse different aspects of reconstruction skill. Canonical Correlation Analysis (CCA), two versions of an Analog Method (AM) and Bayesian hierarchical modeling (BHM) are applied to reconstruct precipitation from a synthetic network of pseudoproxies that are contaminated with various types of noise. The skill of the derived reconstructions is assessed through comparison with precipitation simulated by the regional climate model. Unlike BHM, CCA systematically underestimates the variance. The AM can be adjusted to overcome this shortcoming, presenting an intermediate behaviour between the two aforementioned techniques. However, a trade-off between reconstruction-target correlations and reconstructed variance is the drawback of all CFR techniques. CCA (BHM) presents the largest (lowest) skill in preserving the temporal evolution, whereas the AM can be tuned to reproduce better correlation at the expense of losing variance. While BHM has been shown to perform well for temperatures, it relies heavily on prescribed spatial correlation lengths. While this assumption is valid for temperature, it is hardly warranted for precipitation. In general, none of the methods outperforms the other. All experiments agree that a dense and regularly distributed proxy network is required to reconstruct precipitation accurately, reflecting its high spatial and temporal variability. This is especially true in summer, when a specifically short de-correlation distance from the proxy location is caused by localised summertime convective precipitation events.

Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

A 49 year hindcast of surface winds over the Iberian Peninsula

The use of hindcast climatic data is quite extended for multiple applications. However, this approach needs the support of a validation process to allow its drawbacks and, therefore, confidence levels to be assessed. In this work, the strategy relies on an hourly wind database resulting from a dynamical downscaling experiment, with a spatial resolution of 10 km, covering the Iberian Peninsula (IP), driven by the ERA40 reanalysis (1959–2001) extended by European Centre for Medium-Range Weather Forecast (ECMWF) analysis (2002–2007) and comprising two main steps. Initially, the skill of the simulation is evaluated comparing the quality-tested observational database (Lorente-Plazas et al., 2014) at local and regional scales. The results show that the model is able to portray the main features of the wind over the IP: annual cycles, wind roses, spatial and temporal variability, as well as the response to different circulation types. In addition, there is a significant added value of the simulation with respect to driving conditions, especially in regions with a complex orography. However, some problems are evident, the major drawback being the systematic overestimation of the wind speed, which is mainly attributed to a missrepresentation of frictional forces. The model skill is also lower along the Mediterranean coast and for the Pyrenees. In a second phase, the high spatio-temporal resolution of the pseudo-real wind database is used to explore the limitations of the observational database. It is shown that missing values do not affect the characterisation of the wind climate over the IP, while the length of the observational period (6 years) is sufficient for most regions, with only a few exceptions. The spatial distribution of the observational sampling schemes should be enhanced to improve the correct assessment of all IP wind regimes, particularly in some mountainous areas.

Attributing trends in extremely hot days to changes in atmospheric dynamics

This paper presents a method for attributing regional trends in the frequency of extremely hot days (EHDs) to changes in the frequency of the atmospheric patterns that characterize such extraordinary events. The study is applied to mainland Spain and the Balearic Islands for the extended summers of the period 1958–2008, where significant and positive trends in maximum temperature (Tx) have been reported during the second half of the past century. First, the study area was split into eight regions attending to their different temporal variability of the daily Tx series obtained from the Spain02 gridded data set using a clustering procedure. Second, the large-scale atmospheric situations causing EHDs are defined by circulation types (CTs). The obtainment of the CTs differs from the majority of CT classifications proposed in the literature. It is based on regional series and on a previous characterization of the main atmospheric situations obtained using only some days classified as extremes in the different regions. Three different atmospheric fields (SLP, T850, and Z500) from ECMWF reanalysis and analysis data and combinations of them (SLP–T850, SLP–Z500, and T850–Z500) are used to produce six different CT classifications. Subsequently, links between EHD occurrence in the different regions and CT for all days have been established. Finally, a simple model to relate the trends in EHDsfor each region to the changes in the CT frequency appearance has been formulated. Most regions present positive and significant trends in the occurrence of EHDs. The CT classifications using two variables perform better. In particular, SLP–T850 is the best for characterizing the atmospheric situations leading to EHD occurrences for most of the regions. Only a small number of CTs have significant trends in their frequency and are associated with high efficiency causing EHD occurrences in most regions simultaneously, especially in the northern and central regions. Attribution results show that changes in circulation can only explain some part of the regional EHD trends. The percentage of the trend attributable to changes in atmospheric dynamics varies from 15 to 50 %, depends on the region and is sensitive to the selected large-scale variables.

Soil and land information: How to support decision-making?

Soils are fundamental to ensuring water, energy and food security. Within the context of sus- tainable food production, it is important to share knowledge on existing and emerging tech- nologies that support land and soil monitoring. Technologies, such as remote sensing, mobile soil testing, and digital soil mapping, have the potential to identify degraded and non- /little-responsive soils, and may also provide a basis for programmes targeting the protection and rehabilitation of soils. In the absence of such information, crop production assessments are often not based on the spatio-temporal variability in soil characteristics. In addition, uncertain- ties in soil information systems are notable and build up when predictions are used for monitor- ing soil properties or biophysical modelling. Consequently, interpretations of model-based results have to be done cautiously. As such they provide a scientific, but not always manage- able, basis for farmers and/or policymakers. In general, the key incentives for stakeholders to aim for sustainable management of soils and more resilient food systems are complex at farm as well as higher levels. The same is true of drivers of soil degradation. The decision- making process aimed at sustainable soil management, be that at farm or higher level, also in- volves other goals and objectives valued by stakeholders, e.g. land governance, improved envi- ronmental quality, climate change adaptation and mitigation etc. In this dialogue session we will share ideas on recent developments in the discourse on soils, their functions and the role of soil and land information in enhancing food system resilience.

Alteration of natural ³⁷Ar activity concentration in the subsurface by gas transport and water infiltration

High ³⁷Ar activity concentration in soil gas is proposed as a key evidence for the detection of underground nuclear explosion by the Comprehensive Nuclear Test-Ban Treaty. However, such a detection is challenged by the natural background of ³⁷Ar in the subsurface, mainly due to Ca activation by cosmic rays. A better understanding and improved capability to predict ³⁷Ar activity concentration in the subsurface and its spatial and temporal variability is thus required. A numerical model integrating ³⁷Ar production and transport in the subsurface is developed, including variable soil water content and water infiltration at the surface. A parameterized equation for ³⁷Ar production in the first 15 m below the surface is studied, taking into account the major production reactions and the moderation effect of soil water content. Using sensitivity analysis and uncertainty quantification, a realistic and comprehensive probability distribution of natural ³⁷Ar activity concentrations in soil gas is proposed, including the effects of water infiltration. Site location and soil composition are identified as the parameters allowing for a most effective reduction of the possible range of ³⁷Ar activity concentrations. The influence of soil water content on ³⁷Ar production is shown to be negligible to first order, while ³⁷Ar activity concentration in soil gas and its temporal variability appear to be strongly influenced by transient water infiltration events. These results will be used as a basis for practical CTBTO concepts of operation during an OSI.

Coastal upwelling is linked to temporal genetic variability in the acorn barnacle Balanus glandula

Dispersal and recruitment are central processes that shape the geographic and temporal distributions of populations of marine organisms. However, significant variability in factors such as reproductive output, larval transport, survival, and settlement success can alter the genetic identity of recruits from year to year. We designed a temporal and spatial sampling protocol to test for genetic heterogeneity among adults and recruits from multiple time points along a similar to 400 km stretch of the Oregon (USA) coastline. In total, 2824 adult and recruiting Balanus glandula were sampled between 2001 and 2008 from 9 sites spanning the Oregon coast. Consistent with previous studies, we observed high mitochondrial DNA diversity at the cytochrome oxidase I locus (884 unique haplotypes) and little to no spatial genetic population structure among the 9 sites (Phi(ST) = 0.00026, p = 0.170). However, subtle but significant temporal shifts in genetic composition were observed among year classes (Phi(ST) = 0.00071, p = 0.035), and spatial Phi(ST) varied from year to year. These temporal shifts in genetic structure were correlated with yearly differences in the strength of coastal upwelling (p = 0.002), with greater population structure observed in years with weaker upwelling. Higher levels of barnacle settlement were also observed in years with weaker upwelling (p < 0.001). These data suggest the hypothesis that low upwelling intensity maintains more local larvae close to shore, thereby shaping the genetic structure and settlement rate of recruitment year classes.

Temporal and spatial variability of personal exposure to radio frequency electromagnetic fields

BACKGROUND: Little is known about the population's exposure to radio frequency electromagnetic fields (RF-EMF) in industrialized countries. OBJECTIVES: To examine levels of exposure and the importance of different RF-EMF sources and settings in a sample of volunteers living in a Swiss city. METHODS: RF-EMF exposure of 166 volunteers from Basel, Switzerland, was measured with personal exposure meters (exposimeters). Participants carried an exposimeter for 1 week (two separate weeks in 32 participants) and completed an activity diary. Mean values were calculated using the robust regression on order statistics (ROS) method. RESULTS: Mean weekly exposure to all RF-EMF sources was 0.13 mW/m(2) (0.22 V/m) (range of individual means 0.014-0.881 mW/m(2)). Exposure was mainly due to mobile phone base stations (32.0%), mobile phone handsets (29.1%) and digital enhanced cordless telecommunications (DECT) phones (22.7%). Persons owning a DECT phone (total mean 0.15 mW/m(2)) or mobile phone (0.14 mW/m(2)) were exposed more than those not owning a DECT or mobile phone (0.10 mW/m(2)). Mean values were highest in trains (1.16 mW/m(2)), airports (0.74 mW/m(2)) and tramways or buses (0.36 mW/m(2)), and higher during daytime (0.16 mW/m(2)) than nighttime (0.08 mW/m(2)). The Spearman correlation coefficient between mean exposure in the first and second week was 0.61. CONCLUSIONS: Exposure to RF-EMF varied considerably between persons and locations but was fairly consistent within persons. Mobile phone handsets, mobile phone base stations and cordless phones were important sources of exposure in urban Switzerland.

Impact of above- and below-ground invertebrates on temporal and spatial stability of grassland of different diversity

1. Recent theoretical studies suggest that the stability of ecosystem processes is not governed by diversity per se, but by multitrophic interactions in complex communities. However, experimental evidence supporting this assumption is scarce.2. We investigated the impact of plant diversity and the presence of above- and below-ground invertebrates on the stability of plant community productivity in space and time, as well as the interrelationship between both stability measures in experimental grassland communities.3. We sampled above-ground plant biomass on subplots with manipulated above- and below-ground invertebrate densities of a grassland biodiversity experiment (Jena Experiment) 1, 4 and 6 years after the establishment of the treatments to investigate temporal stability. Moreover, we harvested spatial replicates at the last sampling date to explore spatial stability.4. The coefficient of variation of spatial and temporal replicates served as a proxy for ecosystem stability. Both spatial and temporal stability increased to a similar extent with plant diversity. Moreover, there was a positive correlation between spatial and temporal stability, and elevated plant density might be a crucial factor governing the stability of diverse plant communities.5. Above-ground insects generally increased temporal stability, whereas impacts of both earthworms and above-ground insects depended on plant species richness and the presence of grasses. These results suggest that inconsistent results of previous studies on the diversity–stability relationship have in part been due to neglecting higher trophic-level interactions governing ecosystem stability.6. Changes in plant species diversity in one trophic level are thus unlikely to mirror changes in multitrophic interrelationships. Our results suggest that both above- and below-ground invertebrates decouple the relationship between spatial and temporal stability of plant community productivity by differently affecting the homogenizing mechanisms of plants in diverse plant communities.7.Synthesis. Species extinctions and accompanying changes in multitrophic interactions are likely to result not only in alterations in the magnitude of ecosystem functions but also in its variability complicating the assessment and prediction of consequences of current biodiversity loss.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.