Net CO 2 surface emissions at Bern, Switzerland inferred from ambient observations of CO 2 , δ(O 2 /N 2 ), and 222 Rn using a customized radon tracer inversion

The 222Radon tracer method is a powerful tool to estimate local and regional surface emissions of, e.g., greenhouse gases. In this paper we demonstrate that in practice, the method as it is commonly used, produces inaccurate results in case of nonhomogeneously spread emission sources, and we propose a different approach to account for this. We have applied the new methodology to ambient observations of CO2 and 222Radon to estimate CO2 surface emissions for the city of Bern, Switzerland. Furthermore, by utilizing combined measurements of CO2 and δ(O2/N2) we obtain valuable information about the spatial and temporal variability of the main emission sources. Mean net CO2 emissions based on 2 years of observations are estimated at (11.2 ± 2.9) kt km−2 a−1. Oxidative ratios indicate a significant influence from the regional biosphere in summer/spring and fossil fuel combustion processes in winter/autumn. Our data indicate that the emissions from fossil fuels are, to a large degree, related to the combustion of natural gas which is used for heating purposes.

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).

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.

Observations of the northern seasonal polar cap on Mars III: CRISM/HiRISE observations of spring sublimation

We analyze a series of targeted CRISM and HiRISE observations of seven regions of interest at high latitudes in the Northern polar regions of Mars. These data allow us to investigate the temporal evolution of the composition of the seasonal ice cap during spring, with a special emphasis on peculiar phenomena occurring in the dune fields and in the vicinity of the scarps of the North Polar Layered Deposits (NPLDs). The strength of the spectral signature of CO2 ice continuously decreases during spring whereas the one of H2O ice first shows a strong increase until Ls = 50°. This evolution is consistent with a scenario previously established from analysis of OMEGA data, in which a thin layer of pure H2O ice progressively develops at the surface of the volatile layer. During early spring (Ls < 10°), widespread jet activity is observed by HiRISE while strong spectral signatures of CO2 ice are detected by CRISM. Later, around Ls = 20-40°, activity concentrates at the dune fields where CRISM also detects a spectral enrichment in CO2 ice, consistent with "Kieffer's model" (Kieffer, H.H. [2007]. J. Geophys. Res. 112, E08005. doi:10.1029/2006JE002816) for jet activity. Effects of wind are prominent across the dune fields and seem to strongly influence the sublimation of the volatile layer. Strong winds blowing down the scarps could also be responsible for the significant spatial and temporal variability of the surface ice composition observed close to the NPLD.

Observation errors in early historical upper-air observations

Upper-air observations are a fundamental data source for global atmospheric data products, but uncertainties, particularly in the early years, are not well known. Most of the early observations, which have now been digitized, are prone to a large variety of undocumented uncertainties (errors) that need to be quantified, e.g., for their assimilation in reanalysis projects. We apply a novel approach to estimate errors in upper-air temperature, geopotential height, and wind observations from the Comprehensive Historical Upper-Air Network for the time period from 1923 to 1966. We distinguish between random errors, biases, and a term that quantifies the representativity of the observations. The method is based on a comparison of neighboring observations and is hence independent of metadata, making it applicable to a wide scope of observational data sets. The estimated mean random errors for all observations within the study period are 1.5 K for air temperature, 1.3 hPa for pressure, 3.0 ms−1for wind speed, and 21.4° for wind direction. The estimates are compared to results of previous studies and analyzed with respect to their spatial and temporal variability.

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.

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.

Combining spatial-temporal and phylogenetic analysis approaches for improved understanding on global H5N1 transmission

Background Since late 2003, the highly pathogenic influenza A H5N1 had initiated several outbreak waves that swept across the Eurasia and Africa continents. Getting prepared for reassortment or mutation of H5N1 viruses has become a global priority. Although the spreading mechanism of H5N1 has been studied from different perspectives, its main transmission agents and spread route problems remain unsolved. Methodology/Principal Findings Based on a compilation of the time and location of global H5N1 outbreaks from November 2003 to December 2006, we report an interdisciplinary effort that combines the geospatial informatics approach with a bioinformatics approach to form an improved understanding on the transmission mechanisms of H5N1 virus. Through a spherical coordinate based analysis, which is not conventionally done in geographical analyses, we reveal obvious spatial and temporal clusters of global H5N1 cases on different scales, which we consider to be associated with two different transmission modes of H5N1 viruses. Then through an interdisciplinary study of both geographic and phylogenetic analysis, we obtain a H5N1 spreading route map. Our results provide insight on competing hypotheses as to which avian hosts are responsible for the spread of H5N1. Conclusions/Significance We found that although South China and Southeast Asia may be the virus pool of avian flu, East Siberia may be the source of the H5N1 epidemic. The concentration of migratory birds from different places increases the possibility of gene mutation. Special attention should be paid to East Siberia, Middle Siberia and South China for improved surveillance of H5N1 viruses and monitoring of migratory birds.

Spatial and functional relationships between air conduits and blood capillaries in the pulmonary gas exchange tissue of adult and developing chickens

The documented data regarding the three-dimensional structure of the air capillaries (ACs), the ultimate sites of gas exchange in the avian lung is contradictory. Further, the mode of gas exchange, described as cross-current has not been clearly elucidated. We studied the temporal and spatial arrangement of the terminal air conduits of the chicken lung and their relationship with the blood capillaries (BCs) in embryos as well as the definitive architecture in adults. Several visualization techniques that included corrosion casting, light microscopy as well as scanning and transmission electron microscopy were used. Two to six infundibulae extend from each atrium and give rise to numerous ACs that spread centrifugally. Majority of the ACs are tubular structures that give off branches, which anastomose with their neighboring cognates. Some ACs have globular shapes and a few are blind-ending tapering tubes. During inauguration, the luminal aspects of the ACs are characterized by numerous microvillus-like microplicae, which are formed during the complex processes of cell attenuation and canalization of the ACs. The parabronchial exchange BCs, initially inaugurated as disorganized meshworks, are reoriented via pillar formation to lie predominantly orthogonal to the long axes of the ACs. The remodeling of the retiform meshworks by intussusceptive angiogenesis essentially accomplishes a cross-current system at the gas exchange interface in the adults, where BCs form ring-like patterns around the ACs, thus establishing a cross-current system. Our findings clarify the mode of gas exchange in the parabronchial mantle and illuminate the basis for the functional efficiency of the avian lung.

PM(10) remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV∼ 0.7, rMOD∼ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.

Landscape mosaics maps as a basis for spatial assessment and negotiation of ecosystem services and their trade-offs at the meso-scale: Examples from Laos, Madagascar and China

Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.