Suprathermal electron flux peaks at stream interfaces: Signature of solar wind dynamics or tracer for open magnetic flux transport on the Sun?

The high variability of the intensity of suprathermal electron flux in the solar wind is usually ascribed to the high variability of sources on the Sun. Here we demonstrate that a substantial amount of the variability arises from peaks in stream interaction regions, where fast wind runs into slow wind and creates a pressure ridge at the interface. Superposed epoch analysis centered on stream interfaces in 26 interaction regions previously identified in Wind data reveal a twofold increase in 250 eV flux (integrated over pitch angle). Whether the peaks result from the compression there or are solar signatures of the coronal hole boundary, to which interfaces may map, is an open question. Suggestive of the latter, some cases show a displacement between the electron and magnetic field peaks at the interface. Since solar information is transmitted to 1 AU much more quickly by suprathermal electrons compared to convected plasma signatures, the displacement may imply a shift in the coronal hole boundary through transport of open magnetic flux via interchange reconnection. If so, however, the fact that displacements occur in both directions and that the electron and field peaks in the superposed epoch analysis are nearly coincident indicate that any systematic transport expected from differential solar rotation is overwhelmed by a random pattern, possibly owing to transport across a ragged coronal hole boundary.

Link between DOC in near surface peat and stream water in an upland catchment

Hydrologic transport of dissolved organic carbon (DOC) from peat soils may differ to organo-mineral soils in how they responded to changes in flow, because of differences in soil profile and hydrology. In well-drained organo-mineral soils, low flow is through the lower mineral layer where DOC is absorbed and high flow is through the upper organic layer where DOC is produced. DOC concentrations in streams draining organo-mineral soils typically increase with flow. In saturated peat soils, both high and low flows are through an organic layer where DOC is produced. Therefore, DOC in stream water draining peat may not increase in response to changes in flow as there is no switch in flow path between a mineral and organic layer. To verify this, we conducted a high-resolution monitoring study of soil and stream water at an upland peat catchment in northern England. Our data showed a strong positive correlation between DOC concentrations at − 1 and − 5 cm depth and stream water, and weaker correlations between concentrations at − 20 to − 50 cm depth and stream water. Although near surface organic material appears to be the key source of stream water DOC in both peat and organo-mineral soils, we observed a negative correlation between stream flow and DOC concentrations instead of a positive correlation as DOC released from organic layers during low and high flow was diluted by rainfall. The differences in DOC transport processes between peat and organo-mineral soils have different implications for our understanding of long-term changes in DOC exports. While increased rainfall may cause an increase in DOC flux from peat due to an increase in water volume, it may cause a decrease in concentrations. This response is contrary to expected changes in DOC exports from organo-mineral soils, where increase rainfall is likely to result in an increase in flux and concentration.

Threshold-free object and ground point separation in LIDAR data

Light Detection And Ranging (LIDAR) is an important modality in terrain and land surveying for many environmental, engineering and civil applications. This paper presents the framework for a recently developed unsupervised classification algorithm called Skewness Balancing for object and ground point separation in airborne LIDAR data. The main advantages of the algorithm are threshold-freedom and independence from LIDAR data format and resolution, while preserving object and terrain details. The framework for Skewness Balancing has been built in this contribution with a prediction model in which unknown LIDAR tiles can be categorised as “hilly” or “moderate” terrains. Accuracy assessment of the model is carried out using cross-validation with an overall accuracy of 95%. An extension to the algorithm is developed to address the overclassification issue for hilly terrain. For moderate terrain, the results show that from the classified tiles detached objects (buildings and vegetation) and attached objects (bridges and motorway junctions) are separated from bare earth (ground, roads and yards) which makes Skewness Balancing ideal to be integrated into geographic information system (GIS) software packages.

An analysis of long-term trends, seasonality and short-term dynamics in water quality data from Plynlimon, Wales

This paper examines two hydrochemical time-series derived from stream samples taken in the Upper Hafren catchment, Plynlimon, Wales. One time-series comprises data collected at 7-hour intervals over 22 months (Neal et al., submitted, this issue), while the other is based on weekly sampling over 20 years. A subset of determinands: aluminium, calcium, chloride, conductivity, dissolved organic carbon, iron, nitrate, pH, silicon and sulphate are examined within a framework of non-stationary time-series analysis to identify determinand trends, seasonality and short-term dynamics. The results demonstrate that both long-term and high-frequency monitoring provide valuable and unique insights into the hydrochemistry of a catchment. The long-term data allowed analysis of long-termtrends, demonstrating continued increases in DOC concentrations accompanied by declining SO4 concentrations within the stream, and provided new insights into the changing amplitude and phase of the seasonality of the determinands such as DOC and Al. Additionally, these data proved invaluable for placing the short-term variability demonstrated within the high-frequency data within context. The 7-hour data highlighted complex diurnal cycles for NO3, Ca and Fe with cycles displaying changes in phase and amplitude on a seasonal basis. The high-frequency data also demonstrated the need to consider the impact that the time of sample collection can have on the summary statistics of the data and also that sampling during the hours of darkness provides additional hydrochemical information for determinands which exhibit pronounced diurnal variability. Moving forward, this research demonstrates the need for both long-term and high-frequency monitoring to facilitate a full and accurate understanding of catchment hydrochemical dynamics.

Performance analysis of data transmissions in MPLS and non-MPLS networks

Basic Network transactions specifies that datagram from source to destination is routed through numerous routers and paths depending on the available free and uncongested paths which results in the transmission route being too long, thus incurring greater delay, jitter, congestion and reduced throughput. One of the major problems of packet switched networks is the cell delay variation or jitter. This cell delay variation is due to the queuing delay depending on the applied loading conditions. The effect of delay, jitter accumulation due to the number of nodes along transmission routes and dropped packets adds further complexity to multimedia traffic because there is no guarantee that each traffic stream will be delivered according to its own jitter constraints therefore there is the need to analyze the effects of jitter. IP routers enable a single path for the transmission of all packets. On the other hand, Multi-Protocol Label Switching (MPLS) allows separation of packet forwarding and routing characteristics to enable packets to use the appropriate routes and also optimize and control the behavior of transmission paths. Thus correcting some of the shortfalls associated with IP routing. Therefore MPLS has been utilized in the analysis for effective transmission through the various networks. This paper analyzes the effect of delay, congestion, interference, jitter and packet loss in the transmission of signals from source to destination. In effect the impact of link failures, repair paths in the various physical topologies namely bus, star, mesh and hybrid topologies are all analyzed based on standard network conditions.

Stream water quality and nutrient export in the Slapton Catchments

A weekly programme of water quality monitoring has been conducted by Slapton Ley Field Centre since 1970. Samples have been collected for the four main streams draining into Slapton Ley, from the Ley itself and from other sites within the catchment. On occasions, more frequent sampling has been undertaken during short-term research projects, usually in relation to nutrient export from the catchment. These water quality data, unparalleled in length for a series of small drainage basins in the British Isles, provide a unique resource for analysis of spatial and temporal variations in stream water quality within an agricultural area. Not surprisingly, given the eutrophic status of the Ley, most attention has focused on the nutrients nitrate and phosphate. A number of approaches to modelling nutrient loss have been attempted, including time series analysis and the application of nutrient export and physically-based models.

A study into the accuracy of using meteorological wind data to estimate turbine generation output

Meteorological (met) station data is used as the basis for a number of influential studies into the impacts of the variability of renewable resources. Real turbine output data is not often easy to acquire, whereas meteorological wind data, supplied at a standardised height of 10 m, is widely available. This data can be extrapolated to a standard turbine height using the wind profile power law and used to simulate the hypothetical power output of a turbine. Utilising a number of met sites in such a manner can develop a model of future wind generation output. However, the accuracy of this extrapolation is strongly dependent on the choice of the wind shear exponent alpha. This paper investigates the accuracy of the simulated generation output compared to reality using a wind farm in North Rhins, Scotland and a nearby met station in West Freugh. The results show that while a single annual average value for alpha may be selected to accurately represent the long term energy generation from a simulated wind farm, there are significant differences between simulation and reality on an hourly power generation basis, with implications for understanding the impact of variability of renewables on short timescales, particularly system balancing and the way that conventional generation may be asked to respond to a high level of variable renewable generation on the grid in the future.

Non-uniform data distribution for communication-efficient parallel clustering

Global communicationrequirements andloadimbalanceof someparalleldataminingalgorithms arethe major obstacles to exploitthe computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication costin parallel data mining algorithms and, in particular, in the k-means algorithm for cluster analysis. In the straightforward parallel formulation of the k-means algorithm, data and computation loads are uniformly distributed over the processing nodes. This approach has excellent load balancing characteristics that may suggest it could scale up to large and extreme-scale parallel computing systems. However, at each iteration step the algorithm requires a global reduction operationwhichhinders thescalabilityoftheapproach.Thisworkstudiesadifferentparallelformulation of the algorithm where the requirement of global communication is removed, while maintaining the same deterministic nature ofthe centralised algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real-world distributed applications or can be induced by means ofmulti-dimensional binary searchtrees. The approachcanalso be extended to accommodate an approximation error which allows a further reduction ofthe communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing element

Interpretation of ageostrophic winds and implications for jet stream maintenance

The use of ageostrophic flow to infer the presence of vertical circulations in the entrances and exits of the climatological jet streams is questioned. Problems of interpretation arise because of the use of different definitions of geostrophy in theoretical studies and in analyses of atmospheric data. The nature and role of the ageostrophic flow based on constant and variable Coriolis parameter definitions of geostrophy vary. In the latter the geostrophic divergence cannot be neglected, so the vertical motion is not associated solely with the ageostrophic flow. Evidence is presented suggesting that ageostrophic flow in the climatological jet streams is primarily determined by the kinematic requirements of wave retrogression rather than by a forcing process. These requirements are largely met by the rotational flow, with the divergent circulations present being geostrophically forced, and so playing a secondary, restoring role.

Ice-stream initiation, duration and thinning on James Ross Island, northern Antarctic Peninsula

Predicting the future response of the Antarctic Ice Sheet to climate change requires an understanding of the ice streams that dominate its dynamics. Here we use cosmogenic isotope exposure-age dating (26Al, 10Be and 36Cl) of erratic boulders on ice-free land on James Ross Island, north-eastern Antarctic Peninsula, to define the evolution of Last Glacial Maximum (LGM) ice in the adjacent Prince Gustav Channel. These data include ice-sheet extent, thickness and dynamical behaviour. Prior to ∼18 ka, the LGM Antarctic Peninsula Ice Sheet extended to the continental shelf-edge and transported erratic boulders onto high-elevation mesas on James Ross Island. After ∼18 ka there was a period of rapid ice-sheet surface-lowering, coincident with the initiation of the Prince Gustav Ice Stream. This timing coincided with rapid increases in atmospheric temperature and eustatic sea-level rise around the Antarctic Peninsula. Collectively, these data provide evidence for a transition from a thick, cold-based LGM Antarctic Peninsula Ice Sheet to a thinner, partially warm-based ice sheet during deglaciation.

How well can we model stream phosphorus concentrations in agricultural catchments?

Mechanistic catchment-scale phosphorus models appear to perform poorly where diffuse sources dominate. We investigate the reasons for this for one model, INCA-P, testing model output against 18 months of daily data in a small Scottish catchment. We examine key model processes and provide recommendations for model improvement and simplification. Improvements to the particulate phosphorus simulation are especially needed. The model evaluation procedure is then generalised to provide a checklist for identifying why model performance may be poor or unreliable, incorporating calibration, data, structural and conceptual challenges. There needs to be greater recognition that current models struggle to produce positive Nash–Sutcliffe statistics in agricultural catchments when evaluated against daily data. Phosphorus modelling is difficult, but models are not as useless as this might suggest. We found a combination of correlation coefficients, bias, a comparison of distributions and a visual assessment of time series a better means of identifying realistic simulations.

Assessing the sensitivities of a distributed snow model to forcing data resolution

Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

Joint data assimilation of satellite reflectance and net ecosystem exchange data constrains ecosystem carbon fluxes at a high-elevation subalpine forest

We utilized an ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to estimate carbon fluxes of gross primary productivity and total ecosystem respiration of a high-elevation coniferous forest. The data assimilation routine incorporated aggregated twice-daily measurements of the net ecosystem exchange of CO2 (NEE) and satellite-based reflectance measurements of the fraction of absorbed photosynthetically active radiation (fAPAR) on an eight-day timescale. From these data we conducted a data assimilation experiment with fifteen different combinations of available data using twice-daily NEE, aggregated annual NEE, eight-day f AP AR, and average annual fAPAR. Model parameters were conditioned on three years of NEE and fAPAR data and results were evaluated to determine the information content from the different combinations of data streams. Across the data assimilation experiments conducted, model selection metrics such as the Bayesian Information Criterion and Deviance Information Criterion obtained minimum values when assimilating average annual fAPAR and twice-daily NEE data. Application of wavelet coherence analyses showed higher correlations between measured and modeled fAPAR on longer timescales ranging from 9 to 12 months. There were strong correlations between measured and modeled NEE (R2, coefficient of determination, 0.86), but correlations between measured and modeled eight-day fAPAR were quite poor (R2 = −0.94). We conclude that this inability to determine fAPAR on eight-day timescale would improve with the considerations of the radiative transfer through the plant canopy. Modeled fluxes when assimilating average annual fAPAR and annual NEE were comparable to corresponding results when assimilating twice-daily NEE, albeit at a greater uncertainty. Our results support the conclusion that for this coniferous forest twice-daily NEE data are a critical measurement stream for the data assimilation. The results from this modeling exercise indicate that for this coniferous forest, average annuals for satellite-based fAPAR measurements paired with annual NEE estimates may provide spatial detail to components of ecosystem carbon fluxes in proximity of eddy covariance towers. Inclusion of other independent data streams in the assimilation will also reduce uncertainty on modeled values.

Soil phosphorus dynamics and phytoavailability from sewage sludge at different stages in a treatment stream

The effect of different stages of sewage sludge treatment on phosphorus (P) dynamics in amended soils was determined using samples of undigested liquid (UL), anaerobically digested liquid (AD) and dewatered anaerobically digested (DC) sludge. Sludges were taken from three points in the same treatment stream and applied to a sandy loam soil in field-based mesocosms at 4, 8 and 16t ha−1 dry solids. Mesocosms were sown with perennial ryegrass (Lolium perenne cv. Melle), and the sward was harvested after 35 and 70 days to determine yield and foliar P concentration. Soils were also sampled during this period to measure P transformations and the activities of acid phosphomonoesterase and phosphodiesterase. Data show that the AD amended soils had the greatest plant-available and foliar P content up to the second harvest, but the UL amended soils had the greatest enzyme activity. Characterisation of control and 16t ha−1 soils and sludge using solution 31P nuclear magnetic resonance (NMR) spectroscopy after NaOH–EDTA extraction revealed that P was predominantly in the inorganic pool in all three sludge samples, with the highest proportion (of the total extracted P) as inorganic P in the anaerobically digested liquid sludge. After sludge incorporation, P was immobilised to organic species. The majority of organic P was in monoester-P forms, while the remainder of organic P (diester P and phosphonate P) was more susceptible to transformations through time and showed variation with sludge type. These results show that application of sewage sludge at rates as low as 4t ha−1 can have a significant nutritional benefit to ryegrass over an initial 35-day growth and subsequent 35-day re-growth periods. Differences in P transformation, and hence nutritional benefit, between sludge types were evident throughout the experiment. Thus, differences in sludge treatment process alter the edaphic mineralisation characteristics of biosolids derived from the same source material.