A Comparison between WCS and OPeNDAP for Making Model Results and Data Products Available through the Internet

Numerical models produce output with a large number of variables, grid cells and time steps. The same applies to algorithms that produce gridded datasets from sparse or abundant raw data. Further use of the resulting data products has been challenging, especially for dissemination outside the institute of origin. Due to the gradually increasing size of data products, simply downloading copies of them is becoming impossible. A gradual transition from traditional download methods to web services is therefore observed. Web services allow for on‐the‐fly access to subsets of data that were hitherto considered as indivisible granules. Here we compare the most mature candidates to serve gridded data through the web: the Open‐source Project for a Network Data Access Protocol (OPeNDAP) and Web Coverage Service (WCS) protocols. In the framework of the new Dutch National Model and Data Centre (NMDC.eu) a distributed data storage has been created by coupling OPeNDAP servers. A WCS service layer is provided for the same data. This allows us to compare OPeNDAP and WCS. Using several use cases, we compare the usability, performance and features of the two protocols.     

Earth Observation Scientific Workflows in a Distributed Computing Environment

Geospatially Enabled Scientific Workflows offer a promising toolset to help researchers in the earth observation domain with many aspects of the scientific process. One such aspect is that of access to distributed earth observation data and computing resources. Earth observation research often utilizes large datasets requiring extensive CPU and memory resources in their processing. These resource intensive processes can be chained; the sequence of processes (and their provenance) makes up a scientific workflow. Despite the exponential growth in capacity of desktop computers, their resources are often insufficient for the scientific workflow processing tasks at hand. By integrating distributed computing capabilities into a geospatially enabled scientific workflow environment, it is possible to provide researchers with a mechanism to overcome the limitations of the desktop computer. Most of the effort on extending scientific workflows with distributed computing capabilities has focused on the web services approach, as exemplified by the OGC's Web Processing Service and by GRID computing. The approach to leveraging distributed computing resources described in this article uses instead remote objects via RPyC and the dynamic properties of the Python programming language. The Vistrails environment has been extended to allow for geospatial processing through the EO4Vistrails package ( http://code.google.com/p/eo4vistrails/ ). In order to allow these geospatial processes to be seamlessly executed on distributed resources such as cloud computing nodes, the Vistrails environment has been extended with both multi‐tasking capabilities and distributed processing capabilities. The multi‐tasking capabilities are required in order to allow Vistrails to run side‐by‐side processes, a capability it does not currently have. The distributed processing capabilities are achieved through the use of remote objects and mobile code through RPyC.     

Freshwater geographies: Experimenting with knowing and doing geography differently

The fair and effective governance of freshwater is an increasingly prominent issue in New Zealand. Emerging from a complex of cultural, economic and biophysical narratives, freshwater geographies are multiple, varied and increasingly acknowledged as worthy of interdisciplinary scrutiny. In this commentary, we reflect on a series of generative spaces that we – as group of postgraduate geographers (plus supporting staff) – created to engage with the multiplicity of freshwater meanings both within and beyond the academy. Through this evolving epistemic‐political project, we significantly reframed our own understandings about what freshwater ‘is’ and how it ought to be governed. By pursuing a deeper understanding of how the world gets made, we expand our ability to know and make it differently.     

Post‐orogenic evolution of the southern Pyrenees: constraints from inverse thermo‐kinematic modelling of low‐temperature thermochronology data

The late‐stage evolution of the southern central Pyrenees has been well documented but controversies remain concerning potential Neogene acceleration of exhumation rates and the influence of tectonic and/or climatic processes. A popular model suggests that the Pyrenees and their southern foreland were buried below a thick succession of conglomerates during the Oligocene, when the basin was endorheic. However, both the amount of post‐orogenic fill and the timing of re‐excavation remain controversial. We address this question by revisiting extensive thermochronological datasets of the Axial Zone. We use an inverse approach that couples the thermo‐kinematic model Pecube and the Neighbourhood inversion algorithm to constrain the history of exhumation and topographic changes since 40 Ma. By comparison with independent geological data, we identified a most probable scenario involving rapid exhumation (>2.5 km Myr^?1) between 37 and 30 Ma followed by a strong decrease to very slow rates (0.02 km Myr^?1) that remain constant until the present. Therefore, the inversion does not require a previously inferred Pliocene acceleration in regional exhumation rates. A clear topographic signal emerges, however: the topography has to be infilled by conglomerates to an elevation of 2.6 km between 40 and 29 Ma and then to remain stable until ca. 9 Ma. We interpret the last stage of the topographic history as recording major incision of the southern Pyrenean wedge, due to the Ebro basin connection to the Mediterranean, well before previously suggested Messinian ages. These results thus demonstrate temporally varying controls of different processes on exhumation: rapid rock uplift in an active orogen during late Eocene, whereas base‐level changes in the foreland basin control the post‐orogenic evolution of topography and exhumation in the central Pyrenees. In contrast, climate changes appear to play a lesser role in the post‐orogenic topographic and erosional evolution of this mountain belt.     

Spatially-Averaged Temperature Structure Parameter Over a Heterogeneous Surface Measured by an Unmanned Aerial Vehicle

The structure parameter of temperature, \({C_{T}^{2}}\) , in the lower convective boundary layer was measured using the unmanned mini aerial vehicle M²AV. The measurements were carried out on two hot summer days in July 2010 over a heterogeneous land surface around the boundary-layer field site of the Lindenberg Meteorological Observatory—Richard-Aßmann-Observatory of the German Meteorological Service. The spatial series of \({C_{T}^{2}}\) showed considerable variability along the flight path that was caused by both temporal variations and surface heterogeneity. Comparison of the aircraft data with \({C_{T}^{2}}\) values derived from tower-based in situ turbulence measurements showed good agreement with respect to the diurnal variability. The decrease of \({C_{T}^{2}}\) with height as predicted by free-convection scaling could be confirmed for the morning and afternoon flights while the flights around noon suggest a different behaviour.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Decadal prediction skill in a multi-model ensemble

Decadal climate predictions may have skill due to predictable components in boundary conditions (mainly greenhouse gas concentrations but also tropospheric and stratospheric aerosol distributions) and initial conditions (mainly the ocean state). We investigate the skill of temperature and precipitation hindcasts from a multi-model ensemble of four climate forecast systems based on coupled ocean-atmosphere models. Regional variations in skill with and without trend are compared with similarly analysed uninitialised experiments to separate the trend due to monotonically increasing forcings from fluctuations around the trend due to the ocean initial state and aerosol forcings. In temperature most of the skill in both multi-model ensembles comes from the externally forced trends. The rise of the global mean temperature is represented well in the initialised hindcasts, but variations around the trend show little skill beyond the first year due to the absence of volcanic aerosols in the hindcasts and the unpredictability of ENSO. The models have non-trivial skill in hindcasts of North Atlantic sea surface temperature beyond the trend. This skill is highest in the northern North Atlantic in initialised experiments and in the subtropical North Atlantic in uninitialised simulations. A similar result is found in the Pacific Ocean, although the signal is less clear. The uninitialised simulations have good skill beyond the trend in the western North Pacific. The initialised experiments show some skill in the decadal ENSO region in the eastern Pacific, in agreement with previous studies. However, the results in this study are not statistically significant (p?≈?0.1) by themselves. The initialised models also show some skill in forecasting 4-year mean Sahel rainfall at lead times of 1 and 5?years, in agreement with the observed teleconnection from the Atlantic Ocean. Again, the skill is not statistically significant (p?≈?0.2). Furthermore, uninitialised simulations that include volcanic aerosols have similar skill. It is therefore still an open question whether initialisation improves predictions of Sahel rainfall. We conclude that the main source of skill in forecasting temperature is the trend forced by rising greenhouse gas concentrations. The ocean initial state contributes to skill in some regions, but variations in boundary forcings such as aerosols are as important in decadal forecasting.     

A proposal for a new scenario framework to support research and assessment in different climate research communities

In this paper, we propose a scenario framework that could provide a scenario “thread” through the different climate research communities (climate change – vulnerability, impact, and adaptation - and mitigation) in order to support assessment of mitigation and adaptation strategies and climate impacts. The scenario framework is organized around a matrix with two main axes: radiative forcing levels and socio-economic conditions. The radiative forcing levels (and the associated climate signal) are described by the new Representative Concentration Pathways. The second axis, socio-economic developments comprises elements that affect the capacity for mitigation and adaptation, as well as the exposure to climate impacts. The proposed scenarios derived from this framework are limited in number, allow for comparison across various mitigation and adaptation levels, address a range of vulnerability characteristics, provide information across climate forcing and vulnerability states and span a full century time scale. Assessments based on the proposed scenario framework would strengthen cooperation between integrated-assessment modelers, climate modelers and vulnerability, impact and adaptation researchers, and most importantly, facilitate the development of more consistent and comparable research within and across these research communities.     

Hyperspectral remote sensing of evaporate minerals and associated sediments in Lake Magadi area, Kenya

Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed.Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach (image analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and volcanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows the usefulness of the hypersspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner.     

Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters

Although GNSS techniques are theoretically sensitive to the Earth center of mass, it is often preferable to remove intrinsic origin and scale information from the estimated station positions since they are known to be affected by systematic errors. This is usually done by estimating the parameters of a linearized similarity transformation which relates the quasi-instantaneous frames to a long-term frame such as the International Terrestrial Reference Frame (ITRF). It is well known that non-linear station motions can partially alias into these parameters. We discuss in this paper some procedures that may allow reducing these aliasing effects in the case of the GPS techniques. The options include the use of well-distributed sub-networks for the frame transformation estimation, the use of site loading corrections, a modification of the stochastic model by downweighting heights, or the joint estimation of the low degrees of the deformation field. We confirm that the standard approach consisting of estimating the transformation over the whole network is particularly harmful for the loading signals if the network is not well distributed. Downweighting the height component, using a uniform sub-network, or estimating the deformation field perform similarly in drastically reducing the amplitude of the aliasing effect. The application of these methods to reprocessed GPS terrestrial frames permits an assessment of the level of agreement between GPS and our loading model, which is found to be about 1.5 mm WRMS in height and 0.8 mm WRMS in the horizontal at the annual frequency. Aliased loading signals are not the main source of discrepancies between loading displacement models and GPS position time series.