Preliminary signs of the initiation of deep convection by GNSS

This study reports on the exploitation of GNSS (Global Navigation Satellite System) and a new potential application for weather forecasts and nowcasting. We focus on GPS observations (post-processing with a time resolution of 5 and 15 min and fast calculations with a time resolution of 5 min) and try to establish typical configurations of the water vapour field which characterise convective systems and particularly which supply precursors of their initiation are associated with deep convection. We show the critical role of GNSS horizontal gradients of the water vapour content to detect small scale structures of the troposphere (i. e. convective cells), and then we present our strategy to obtain typical water vapour configurations by GNSS called "H2O alert". These alerts are based on a dry/wet contrast taking place during a 30 min time window before the initiation of a convective system. GNSS observations have been assessed for the rainfall event of 28-29 June 2005 using data from the Belgian dense network (baseline from 5 to 30 km). To validate our GNSS H2O alerts, we use the detection of precipitation by C-band weather radar and thermal infrared radiance (cloud top temperature) of the 10.8-micrometers channel [Ch09] of SEVIRI instrument on Meteosat Second Generation. Using post-processed measurements, our H2O alerts obtain a score of about 80 %. Final and ultra-rapid IGS (International GNSS Service) orbits have been tested and show equivalent results. Fast calculations (less than 10 min) have been processed for 29 June 2005 with a time resolution of 5 min. The mean bias (and standard deviation) between fast and reference post-processed ZTD (zenith total delay) and gradients are, respectively, 0.002 (+/- 0.008) m and 0.001 (+/- 0.004) m. The score obtained for the H2O alerts generated by fast calculations is 65 %

The impacts of environmental warming on Odonata: a review

Climate change brings with it unprecedented rates of increase in environmental temperature, which will have major consequences for the earth's flora and fauna. The Odonata represent a taxon that has many strong links to this abiotic factor due to its tropical evolutionary history and adaptations to temperate climates. Temperature is known to affect odonate physiology including life-history traits such as developmental rate, phenology and seasonal regulation as well as immune function and the production of pigment for thermoregulation. A range of behaviours are likely to be affected which will, in turn, influence other parts of the aquatic ecosystem, primarily through trophic interactions. Temperature may influence changes in geographical distributions, through a shifting of species' fundamental niches, changes in the distribution of suitable habitat and variation in the dispersal ability of species. Finally, such a rapid change in the environment results in a strong selective pressure towards adaptation to cope and the inevitable loss of some populations and, potentially, species. Where data are lacking for odonates, studies on other invertebrate groups will be considered. Finally, directions for research are suggested, particularly laboratory studies that investigate underlying causes of climate-driven macroecological patterns

Species richness declines and biotic homogenization have slowed down for NW-European pollinators and plants

Concern about biodiversity loss has led to increased public investment in conservation. Whereas there is a widespread perception that such initiatives have been unsuccessful, there are few quantitative tests of this perception. Here, we evaluate whether rates of biodiversity change have altered in recent decades in three European countries (Great Britain, Netherlands and Belgium) for plants and flower visiting insects. We compared four 20-year periods, comparing periods of rapid land-use intensification and natural habitat loss (1930–1990) with a period of increased conservation investment (post-1990). We found that extensive species richness loss and biotic homogenisation occurred before 1990, whereas these negative trends became substantially less accentuated during recent decades, being partially reversed for certain taxa (e.g. bees in Great Britain and Netherlands). These results highlight the potential to maintain or even restore current species assemblages (which despite past extinctions are still of great conservation value), at least in regions where large-scale land-use intensification and natural habitat loss has ceased

The distribution of pond snail communities across a landscape: separating out the influence of spatial position from local habitat quality for ponds in south-east Northumberland, UK

Ponds support a rich biodiversity because the heterogeneity of individual ponds creates, at the landscape scale, a diversity of habitats for wildlife. The distribution of pond animals and plants will be influenced by both the local conditions within a pond and the spatial distribution of ponds across the landscape. Separating out the local from the spatial is difficult because the two are often linked. Pond snails are likely to be affected by both local conditions, e.g. water hardness, and spatial patterns, e.g. distance between ponds, but studies of snail communities struggle distinguishing between the two. In this study, communities of snails were recorded from 52 ponds in a biogeographically coherent landscape in north-east England. The distribution of snail communities was compared to local environments characterised by the macrophyte communities within each pond and to the spatial pattern of ponds throughout the landscape. Mantel tests were used to partial out the local versus the landscape respective influences. Snail communities became more similar in ponds that were closer together and in ponds with similar macrophyte communities as both the local and the landscape scale were important for this group of animals. Data were collected from several types of ponds, including those created on nature reserves specifically for wildlife, old field ponds (at least 150 years old) primarily created for watering livestock and subsidence ponds outside protected areas or amongst coastal dunes. No one pond type supported all the species. Larger, deeper ponds on nature reserves had the highest numbers of species within individual ponds but shallow, temporary sites on farm land supported a distinct temporary water fauna. The conservation of pond snails in this region requires a diversity of pond types rather than one idealised type and ponds scattered throughout the area at a variety of sites, not just concentrated on nature reserves

Environmental determinants of macroinvertebrate diversity in small water bodies: insights from tank-bromeliads

The interlocking leaves of tank-forming bromeliads (Bromeliaceae) collect rainwater and detritus, thus creating a freshwater habitat for specialized organisms. Their abundance and the possibility of quantifying communities with accuracy give us unparalleled insight into how changes in local to regional environments influence community diversity in small water bodies. We sampled 365 bromeliads (365 invertebrate communities) along a southeastern to northwestern range in French Guiana. Geographic locality determined the species pool for bromeliad invertebrates, and local environments determined the abundance patterns through the selection of traits that are best adapted to the bromeliad habitats. Patterns in community structure mostly emerged from patterns of predator species occurrence and abundance across local-regional environments, while the set of detritivores remained constant. Water volume had a strong positive correlation with invertebrate diversity, making it a biologically relevant measure of the pools' carrying capacity. The significant effects of incoming detritus and incident light show that changes in local environments (e.g., the conversion of forest to cropping systems) strongly influence freshwater communities. Because changes in local environments do not affect detritivores and predators equally, one may expect functional shifts as sets of invertebrates with particular traits are replaced or complemented by other sets with different traits

Scientific challenges of convective-scale numerical weather prediction

Numerical weather prediction (NWP) models are increasing in resolution and becoming capable of explicitly representing individual convective storms. Is this increase in resolution leading to better forecasts? Unfortunately, we do not have sufficient theoretical understanding about this weather regime to make full use of these NWPs. After extensive efforts over the course of a decade, convective–scale weather forecasts with horizontal grid spacings of 1–5 km are now operational at national weather services around the world, accompanied by ensemble prediction systems (EPSs). However, though already operational, the capacity of forecasts for this scale is still to be fully exploited by overcoming the fundamental difficulty in prediction: the fully three–dimensional and turbulent nature of the atmosphere. The prediction of this scale is totally different from that of the synoptic scale (103 km) with slowly–evolving semi–geostrophic dynamics and relatively long predictability on the order of a few days. Even theoretically, very little is understood about the convective scale compared to our extensive knowledge of the synoptic-scale weather regime as a partial–differential equation system, as well as in terms of the fluid mechanics, predictability, uncertainties, and stochasticity. Furthermore, there is a requirement for a drastic modification of data assimilation methodologies, physics (e.g., microphysics), parameterizations, as well as the numerics for use at the convective scale. We need to focus on more fundamental theoretical issues: the Liouville principle and Bayesian probability for probabilistic forecasts; and more fundamental turbulence research to provide robust numerics for the full variety of turbulent flows. The present essay reviews those basic theoretical challenges as comprehensibly as possible. The breadth of the problems that we face is a challenge in itself: an attempt to reduce these into a single critical agenda should be avoided

Source reconstruction via deposition measurements of an undeclared radiological atmospheric release

Inverse modelling of atmospheric releases of radioactivity consists of reconstructing the release source by combining radiological field measurements with atmospheric transport calculations. This is typically performed with air concentration measurements, although deposition measurements or gamma dose rate measurements could also be used. In this paper, we assess the use of deposition measurements of radioactivity in this context. This is done through a case study of the undisclosed release of the radionuclide 106Ru in Eurasia during the autumn of 2017. The atmospheric transport model we utilize for this purpose is FLEXPART. Inverse modelling is performed with the inverse modelling tool FREAR (Forensic Radionuclide Event Analysis and Reconstruction), which has been modified to work with deposition measurements. The inversion consists of Bayesian and cost-function-based algorithms to reconstruct the initial source properties. Inverse modelling is applied to both real and synthetic-deposition data following the 106Ru release. We also construct synthetic air concentration data for use in inverse modelling to make a comparison with the results using deposition data. It is found that source localization is feasible with both the synthetic and real-world deposition data. Synthetic air concentration measurements lead to more precise source localization than deposition. It is demonstrated that this can be explained by the lower detection limits of air concentration measurements compared to deposition.</p

An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4

Wet deposition plays a crucial role in the removal of aerosols from the atmosphere. Yet, large uncertainties remain in its implementation in atmospheric transport models, specifically in the parameterisation schemes that are often used. Recently, a new wet deposition scheme was introduced in FLEXPART. The input parameters for its wet deposition scheme can be altered by the user and may be case-specific. In this paper, a new method is presented to optimise the wet scavenging rates in atmospheric transport models such as FLEXPART. The optimisation scheme is tested in a case study of aerosol-attached 137Cs following the Fukushima Daiichi nuclear power plant accident. From this, improved values for the wet scavenging input parameters in FLEXPART are suggested.</p

A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks

Detector networks that measure environmental radiation serve as radiological surveillance and early warning networks in many countries across Europe and beyond. Their goal is to detect anomalous radioactive signatures that indicate the release of radionuclides into the environment. Often, the background ambient dose equivalent rate H˙*(10) is predicted using meteorological information. However, in dense detector networks, the correlation between different detectors is expected to contain markedly more information. In this work, we investigate how the joint observations by neighbouring detectors can be leveraged to predict the background H˙*(10). Treating it as a stochastic vector, we show that its distribution can be approximated as multivariate normal. We reframe the question of background prediction as a Bayesian inference problem including priors and likelihood. Finally, we show that the conditional distribution can be used to make predictions. To perform the inferences we use PyMC. All inferences are performed using real data for the nuclear sites in Doel and Mol, Belgium. We validate our calibrated model on previously unseen data. Application of the model to a case with known anomalous behaviour – observations during the operation of Belgian Reactor 1 (BR1) in Mol – highlights the relevance of our method for anomaly detection and quantification.</p

When is the Best Time to Sample Aquatic Macroinvertebrates in Ponds for Biodiversity Assessment?

Ponds are sites of high biodiversity and conservation value, yet there is little or no statutory monitoring of them across most of Europe. There are clear and standardized protocols for sampling aquatic macroinvertebrate communities in ponds but the most suitable time(s) to undertake the survey(s) remains poorly specified. This paper examined the aquatic macroinvertebrate communities from 95 ponds within different landuse types over three seasons (spring, summer and autumn) to determine the most appropriate time to undertake sampling to characterise biodiversity. The combined samples from all three seasons provided the most comprehensive record of the aquatic macroinvertebrate taxa recorded within ponds (alpha and gamma diversity). Samples collected during the autumn survey yielded significantly greater macroinvertebrate richness (76% of the total diversity) than either spring or summer surveys. Macroinvertebrate diversity was greatest during autumn in meadow and agricultural ponds but taxon richness among forest and urban ponds did not differ significantly temporally. The autumn survey provided the highest measures of richness for Coleoptera, Hemiptera and Odonata. However, richness of the aquatic insect order Trichoptera was highest in spring and lowest in autumn. The results illustrate that multiple surveys, covering more than one season, provide the most comprehensive representation of macroinvertebrate biodiversity. When sampling can only be undertaken on one occasion, the most appropriate time to undertake surveys to characterise the macroinvertebrate community biodiversity is during the autumn; although this may need to be modified if other floral and faunal groups need to be incorporated in to the sampling programme