The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

The joint influence of personal achievement goals and classroom goal structures on achievement-relevant outcomes

The authors provide an analytic framework for studying the joint influence of personal achievement goals and classroom goal structures on achievement-relevant outcomes. This framework encompasses 3 models (the direct effect model, indirect effect model, and interaction effect model), each of which addresses a different aspect of the joint influence of the 2 goal levels. These 3 models were examined together with a sample of 1,578 Japanese junior high and high school students from 47 classrooms. Results provided support for each of the 3 models: Classroom goal structures were not only direct, but also indirect predictors of intrinsic motivation and academic self-concept, and some cross-level interactions between personal achievement goals and classroom goal structures were observed (indicating both goal match and goal mismatch effects). A call is made for more research that takes into consideration achievement goals at both personal and structural levels of representation. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr – Part 1: A new geomagnetic data composite

We present a new composite of geomagnetic activity which is designed to be as homogeneous in its construction as possible. This is done by only combining data that, by virtue of the locations of the source observatories used, have similar responses to solar wind and IMF (interplanetary magnetic field) variations. This will enable us (in Part 2, Lockwood et al., 2013a) to use the new index to reconstruct the interplanetary magnetic field, B, back to 1846 with a full analysis of errors. Allowance is made for the effects of secular change in the geomagnetic field. The composite uses interdiurnal variation data from Helsinki for 1845–1890 (inclusive) and 1893–1896 and from Eskdalemuir from 1911 to the present. The gaps are filled using data from the Potsdam (1891–1892 and 1897–1907) and the nearby Seddin observatories (1908–1910) and intercalibration achieved using the Potsdam–Seddin sequence. The new index is termed IDV(1d) because it employs many of the principles of the IDV index derived by Svalgaard and Cliver (2010), inspired by the u index of Bartels (1932); however, we revert to using one-day (1d) means, as employed by Bartels, because the use of near-midnight values in IDV introduces contamination by the substorm current wedge auroral electrojet, giving noise and a dependence on solar wind speed that varies with latitude. The composite is compared with independent, early data from European-sector stations, Greenwich, St Petersburg, Parc St Maur, and Ekaterinburg, as well as the composite u index, compiled from 2–6 stations by Bartels, and the IDV index of Svalgaard and Cliver. Agreement is found to be extremely good in all cases, except two. Firstly, the Greenwich data are shown to have gradually degraded in quality until new instrumentation was installed in 1915. Secondly, we infer that the Bartels u index is increasingly unreliable before about 1886 and overestimates the solar cycle amplitude between 1872 and 1883 and this is amplified in the proxy data used before 1872. This is therefore also true of the IDV index which makes direct use of the u index values.

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr – Part 2: A new reconstruction of the interplanetary magnetic field

We present a new reconstruction of the interplanetary magnetic field (IMF, B) for 1846–2012 with a full analysis of errors, based on the homogeneously constructed IDV(1d)composite of geomagnetic activity presented in Part 1 (Lockwood et al., 2013a). Analysis of the dependence of the commonly used geomagnetic indices on solar wind parameters is presented which helps explain why annual means of interdiurnal range data, such as the new composite, depend only on the IMF with only a very weak influence of the solar wind flow speed. The best results are obtained using a polynomial (rather than a linear) fit of the form B = χ · (IDV(1d) − β)α with best-fit coefficients χ = 3.469, β = 1.393 nT, and α = 0.420. The results are contrasted with the reconstruction of the IMF since 1835 by Svalgaard and Cliver (2010).

Pollen, plant macrofossil and charcoal records for palaeovegetation reconstruction in the Mediterranean-Black Sea Corridor since the Last Glacial Maximum

New reconstructions of changing vegetation patterns in the Mediterranean-Black Sea Corridor since the Last Glacial Maximum are being produced by an improved biomisation scheme that uses both pollen and plant macrofossil data, in conjunction. Changes in fire regimes over the same interval will also be reconstructed using both microscopic and macroscopic charcoal remains. These reconstructions will allow a diagnosis of the interactions between climate, fire and vegetation on millennial timescales, and will also help to clarify the role of coastline and other geomorphic changes, salinity and impacts of human activities in this region. These new data sets are being produced as a result of collaboration between the Palynology Working Group (WG-2) within the IGCP-521 project and the international Palaeovegetation Mapping Project (BIOME 6000). The main objective of this paper is to present the goals of this cooperation, methodology, including limitations and planned improvements, and to show the initial results of some applications.

An integrated multi-stage model of knowledge management in international joint ventures: identifying a trigger for knowledge exploration and knowledge harvest

This paper examines the evolution of knowledge management from the initial knowledge migration stage, through adaptation and creation, to the reverse knowledge migration stage in international joint ventures (IJVs). While many studies have analyzed these stages (mostly focusing on knowledge transfer), we investigated the path-dependent nature of knowledge flow in IJVs. The results from the empirical analysis based on a survey of 136 Korean parent companies of IJVs reveal that knowledge management in IJVs follows a sequential, multi-stage process, and that the knowledge transferred from parents to IJVs must first be adapted within its new environment before it reaches the creation stage. We also found that only created knowledge is transferred back to parents.

Dynamic Devensian ice flow in NE England: a sedimentological reconstruction

This study reconstructs the depositional environments that accompanied both ice advance and ice retreat of the last British–Irish Ice Sheet in NE England during the Last Glacial Maximum, and proposes three regional ice-flow phases. The Late Devensian (29–22 cal. ka BP) Tyne Gap Ice Stream initially deposited the Blackhall Till Formation during shelf-edge glaciation (Phase I). This subglacial traction till comprises several related facies, including stratified and laminated diamictons, tectonites, and sand and gravel beds deposited both in subglacial canals and in proglacial streams. Eventually, stagnation of the Tyne Gap Ice Stream led to ice-marginal sedimentation in County Durham (Phase II). During the Dimlington Stadial (21 cal. ka BP), the North Sea Lobe advanced towards the coastline of N Norfolk. This resulted initially in sandur deposition (widespread, tabular sand and gravel; the Peterlee Sand and Gravel Formation; Phase II) and ultimately in deposition of the Horden Till Formation (Phase III), a massive subglacial till. As the North Sea Lobe overrode previous formations, it thrusted and stacked sediments in County Durham, and dammed proglacial lakes between the east-coast ice, the Pennine uplands and the remaining Pennine ice. The North Sea Lobe retreated after Heinrich Event 1 (16 ka). This study highlights the complexity of ice flow during the Late Devensian glaciation of NE England, with changing environmental and oceanic conditions forcing a mobile and sensitive ice sheet.

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr - Part 4: Near-Earth solar wind speed, IMF, and open solar flux

In the concluding paper of this tetralogy, we here use the different geomagnetic activity indices to reconstruct the near-Earth interplanetary magnetic field (IMF) and solar wind flow speed, as well as the open solar flux (OSF) from 1845 to the present day. The differences in how the various indices vary with near-Earth interplanetary parameters, which are here exploited to separate the effects of the IMF and solar wind speed, are shown to be statistically significant at the 93% level or above. Reconstructions are made using four combinations of different indices, compiled using different data and different algorithms, and the results are almost identical for all parameters. The correction to the aa index required is discussed by comparison with the Ap index from a more extensive network of mid-latitude stations. Data from the Helsinki magnetometer station is used to extend the aa index back to 1845 and the results confirmed by comparison with the nearby St Petersburg observatory. The optimum variations, using all available long-term geomagnetic indices, of the near-Earth IMF and solar wind speed, and of the open solar flux, are presented; all with ±2sigma� uncertainties computed using the Monte Carlo technique outlined in the earlier papers. The open solar flux variation derived is shown to be very similar indeed to that obtained using the method of Lockwood et al. (1999).

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr - Part 3: improved representation of solar cycle 11

Svalgaard (2014) has recently pointed out that the calibration of the Helsinki magnetic observatory’s H component variometer was probably in error in published data for the years 1866–1874.5 and that this makes the interdiurnal variation index based on daily means, IDV(1d), (Lockwood et al., 2013a), and the interplanetary magnetic field strength derived from it (Lockwood et al., 2013b), too low around the peak of solar cycle 11. We use data from the modern Nurmijarvi station, relatively close to the site of the original Helsinki Observatory, to confirm a 30% underestimation in this interval and hence our results are fully consistent with the correction derived by Svalgaard. We show that the best method for recalibration uses the Helsinki Ak(H) and aa indices and is accurate to ±10 %. This makes it preferable to recalibration using either the sunspot number or the diurnal range of geomagnetic activity which we find to be accurate to ±20 %. In the case of Helsinki data during cycle 11, the two recalibration methods produce very similar corrections which are here confirmed using newly digitised data from the nearby St Petersburg observatory and also using declination data from Helsinki. However, we show that the IDV index is, compared to later years, too similar to sunspot number before 1872, revealing independence of the two data series has been lost; either because the geomagnetic data used to compile IDV has been corrected using sunspot numbers, or vice versa, or both. We present corrected data sequences for both the IDV(1d) index and the reconstructed IMF (interplanetary magnetic field).We also analyse the relationship between the derived near-Earth IMF and the sunspot number and point out the relevance of the prior history of solar activity, in addition to the contemporaneous value, to estimating any “floor” value of the near-Earth interplanetary field.

Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach

The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

Revolution blues: the reconstruction of Health and Safety as a ‘common-sense’ form of regulation

This paper provides a review of the last five years of policymaking in the area of health and safety law; this includes multiple reviews, legislative reform, and the reframing of rhetoric around the issue. It characterises this as a process of social construction of a new ‘universe of meaning’ around health and safety regulation, which provides a basis for a particular, narrow, neoliberal conception of regulation and responsibility to permeate the mainstream. Deliberative and public-facing policymaking processes have been utilised as a key element of this process.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soybean, maize and rice. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soybean at the global and country levels, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index, gross primary production and canopy height better than in the standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an Earth system and crop yield model perspective is encouraging. However, more effort is needed to develop the parametrisation of the model for specific applications. Key future model developments identified include the introduction of processes such as irrigation and nitrogen limitation which will enable better representation of the spatial variability in yield.