SEISMICITY of KAZAKHSTAN and ADJACENT TERRITORIES in 2015

In 2015, the seismic monitoring in Kazakhstan was conducted by two Organizations: Seismological Experience-Methodical Expedition of the Ministry of Education and Science of the Republic of Kazakhstan (SEME), and the Republican State Enterprise Institute of Geophysical Research of the Ministry of Energy of the Republic of Kazakhstan (IGR). The paper presents detailed information on seismic observation networks. The joint catalogue based on the data of two organizations was compiled. It includes 489 earthquakes having energy class KR=6.6–12.2. The largest earthquake occurred on January 20, 2015 near the Semipalatinsk Test Site. The earthquake had magnitude MPVA=5.3, energy class KR=12.2, and was felt in a range of Kazakhstan settlements.

The Unmanned Systems Research Laboratory (USRL): A New Facility for UAV-Based Atmospheric Observations

The Unmanned Systems Research Laboratory (USRL) of the Cyprus Institute is a new mobile exploratory platform of the EU Research Infrastructure Aerosol, Clouds and Trace Gases Research InfraStructure (ACTRIS). USRL offers exclusive Unmanned Aerial Vehicle (UAV)-sensor solutions that can be deployed anywhere in Europe and beyond, e.g., during intensive field campaigns through a transnational access scheme in compliance with the drone regulation set by the European Union Aviation Safety Agency (EASA) for the research, innovation, and training. UAV sensor systems play a growing role in the portfolio of Earth observation systems. They can provide cost-effective, spatial in-situ atmospheric observations which are complementary to stationary observation networks. They also have strong potential for calibrating and validating remote-sensing sensors and retrieval algorithms, mapping close-to-the-ground emission point sources and dispersion plumes, and evaluating the performance of atmospheric models. They can provide unique information relevant to the short- and long-range transport of gas and aerosol pollutants, radiative forcing, cloud properties, emission factors and a variety of atmospheric parameters. Since its establishment in 2015, USRL is participating in major international research projects dedicated to (1) the better understanding of aerosol-cloud interactions, (2) the profiling of aerosol optical properties in different atmospheric environments, (3) the vertical distribution of air pollutants in and above the planetary boundary layer, (4) the validation of Aeolus satellite dust products by utilizing novel UAV-balloon-sensor systems, and (5) the chemical characterization of ship and stack emissions. A comprehensive overview of the new UAV-sensor systems developed by USRL and their field deployments is presented here. This paper aims to illustrate the strong scientific potential of UAV-borne measurements in the atmospheric sciences and the need for their integration in Earth observation networks.

The Assessment of Potential Observability for Joint Chemical States and Emissions in Atmospheric Modelings

In predictive geophysical model systems, uncertain initial values and model parameters jointly influence the temporal evolution of the system. As for chemistry-transport models, emission rates are at least as important as initial values for model evolution controls. This renders initial-value-only optimization by traditional data assimilation methods as insufficient. However, blindly extending the optimization parameter set jeopardizes the validity of the resulting analysis since the ill-posedness of the inversion task is increased. Hence, it becomes important to assess the potential observability of measurement networks for model state and parameters in atmospheric modelings in advance of the optimization. In this paper, we introduce an approach to quantify the impact of observation networks jointly for initial trace gas state and emission rates for transport-diffusion models extended by emissions. Applying a Kalman smoother as underlying assimilation technique, we develop a quantitative assessment method to evaluate the potential observability and the sensitivity of observation networks to initial values and emission rates. For practical applications, we derive an ensemble based version of the approach and give several elementary experiments for illustration.

European High Frequency Radar network governance

This report describes the governance of the European HF radar network including: the landscape of the Ocean observation networks and infrastructures, the role and links between operators of observational systems and stakeholders, the role and activities of the EuroGOOS HF radar Task Team in building a sound community strategy, the roadmap of the community with current achievements and future work lines.

The phylogeny of Critical Zone Observatories, or how to better structure existing observation networks to match the whole system approach

<p>Implementing the Whole System Approach for long-term ecosystem, critical zone and socio-ecological system research requires going beyond existing structuration of scientific communities and observation networks. Indeed, existing observation networks were often built independently from each other, on a very disciplinary basis, with their own scientific objectives, funding mechanisms and institutional constraints. To tackle the observation challenges of the “new climatic regime” in the Anthropocene, a new type of observational platforms, more compatible with a scientific systemic approach needs to be built taking into account the history and institutional contexts of long-term observatories.</p><p><br>We have attempted to represent the diversity of critical zone observatories, sites and network of observatories that exist and that have been founded by different research institutions in France over the last 40 years and that are now gathered in the OZCAR Critical Zone network. Our representation encapsulates three main characteristics: the spatial scales of investigation (from the plot scale to the continental-scale watershed), the diversity of monitored compartments (catchments, glaciers, peatlands, aquifers…), and the institutional dimension (labeling and founding at the national level).  We found that a representation in the form of a tree, mimicking the phylogenetic tree of life, named the OZCAR-tree, was offering a visualization tool able to capture the philosophy and rationale of the network and was useful to improve the communication with the neighboring infrastructures, users and stakeholders. The branches of the tree represent the nested monitored scales, with the small branches of the tree representing monitored parcels or small catchments. The trunks represent networks of sites investigating the same compartment. For monitored catchments, the representation directly shows the various sampled scales and their nested organization from upstream to downstream. At each site, colored pie charts allow us to visualize rapidly the types of data that are collected, each part of the pie being a component of the critical zone (atmosphere, soil water, aquifers, vegetation, snow, ice…). This visualization directly shows the focus of the various sites, the completeness of measurements conducted by the different scientists, but also the missing compartments. It also shows that, if the network, as a whole is able to sample the various compartments and variables required for implementing the whole system approach, it is rarely the case when considering individual sites.</p><p>Beyond being a visualization tool, the OZCAR-tree helps representing the requirements of a “whole critical zone approach”. Because all compartments of the critical zone are connected vertically and horizontally by processes and fluxes of energy and matter, the tree is meant to represent all the components to be monitored and what should be the spatial architecture of a monitoring network fulfilling the disciplinary questions and approaches. The tree is therefore an illustration of a conceptual and idealized network (devoid of cost issues) of terrestrial surfaces monitoring infrastructure respectful of disciplinary approaches.</p><p>Finally, this representation is open to ecological and socio-ecological communities and may serve as a template for fostering collaboration with ecological and socio-ecological communities and networks and implementing observation platforms at the scale of changing territories.</p>

Verification of Regional Deterministic Precipitation Analysis products using snow data assimilation for application in meteorological network assessment in sparsely gauged Nordic basins

Sparse precipitation information can result in uncertainties in hydrological modelling practices. Precipitation observation network augmentation is one way to reduce the uncertainty. Meanwhile, in basins with snowpack-dominated hydrology, in the absence of a high-density precipitation observation network, assimilation of in situ and remotely sensed measurements of snowpack state variables can also provide the possibility to reduce flow estimation uncertainty. Similarly, assimilation of existing precipitation observations into gridded numerical precipitation products can alleviate the adverse effects of missing information in poorly instrumented basins. In Canada, the Regional Deterministic Precipitation Analysis (RDPA) data from the Canadian Precipitation Analysis (CaPA) system have been increasingly applied for flow estimation in sparsely gauged Nordic basins. Moreover, CaPA-RDPA data have also been applied to establish observational priorities for augmenting precipitation observation networks. However, the accuracy of the assimilated data should be validated before being applicable in observation network assessment. The assimilation of snowpack state variables has proven to significantly improve streamflow estimates, and therefore, it can provide the benchmark against which the impact of assimilated precipitation data on streamflow simulation can be compared. Therefore, this study introduces a parsimonious framework for performing a proxy-validation of the precipitation assimilated products through the application of snow assimilation in physically-based hydrologic models. This framework is demonstrated to assess the observation networks in three boreal basins in Yukon, Canada. The results indicate that in most basins, the gridded analysis products generally enjoyed the level of accuracy required for accurate flow simulation and therefore were applied in the meteorological network assessment in those cases.

Novel Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Data

Global loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding of underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts.