Vertical distribution, size and composition of the weed seedbank under various tillage and herbicide treatments in a sequence of industrial crops

Investigations were conducted during the 2003, 2004 and 2005 growing seasons in northern Greece to evaluate effects of tillage regime (mouldboard plough, chisel plough and rotary tiller), cropping sequence (continuous cotton, cotton-sugar beet rotation and continuous tobacco) and herbicide treatment on weed seedbank dynamics. Amaranthus spp. and Portulaca oleracea were the most abundant species, ranging from 76% to 89% of total weed seeds found in 0-15 and 15-30 cm soil depths during the 3 years. With the mouldboard plough, 48% and 52% of the weed seedbank was found in the 0-15 and 15-30 cm soil horizons, while approximately 60% was concentrated in the upper 15 cm soil horizon for chisel plough and rotary tillage. Mouldboard ploughing significantly buried more Echinochloa crus-galli seeds in the 15-30 cm soil horizon compared with the other tillage regimes. Total seedbank (0-30 cm) of P. oleracea was significantly reduced in cotton-sugar beet rotation compared with cotton and tobacco monocultures, while the opposite occurred for E. crus-galli. Total seed densities of most annual broad-leaved weed species (Amaranthus spp., P. oleracea, Solanum nigrum) and E. crus-galli were lower in herbicide treated than in untreated plots. The results suggest that in light textured soils, conventional tillage with herbicide use gradually reduces seed density of small seeded weed species in the top 15 cm over several years. In contrast, crop rotation with the early established sugar beet favours spring-germinating grass weed species, but also prevents establishment of summer-germinating weed species by the early developing crop canopy.

On the system of rational difference equations x(n) = A+(1)over-bar y(n-p), y(n) = A+(gamma(n-1))over-bar x(n-r)y(n-5)

In this paper, we study the behavior of the positive solutions of the system of two difference equations [GRAPHICS] where p >= 1, r >= 1, s >= 1, A >= 0, and x(1-r), x(2-r),..., x(0), y(1-max) {p.s},..., y(0) are positive real numbers. (c) 2005 Elsevier Inc. All rights reserved.

Effect of improving representation of horizontal and vertical cloud structure on the Earth's global radiation budget. Part I: review and parametrization

A poor representation of cloud structure in a general circulation model (GCM) is widely recognised as a potential source of error in the radiation budget. Here, we develop a new way of representing both horizontal and vertical cloud structure in a radiation scheme. This combines the ‘Tripleclouds’ parametrization, which introduces inhomogeneity by using two cloudy regions in each layer as opposed to one, each with different water content values, with ‘exponential-random’ overlap, in which clouds in adjacent layers are not overlapped maximally, but according to a vertical decorrelation scale. This paper, Part I of two, aims to parametrize the two effects such that they can be used in a GCM. To achieve this, we first review a number of studies for a globally applicable value of fractional standard deviation of water content for use in Tripleclouds. We obtain a value of 0.75 ± 0.18 from a variety of different types of observations, with no apparent dependence on cloud type or gridbox size. Then, through a second short review, we create a parametrization of decorrelation scale for use in exponential-random overlap, which varies the scale linearly with latitude from 2.9 km at the Equator to 0.4 km at the poles. When applied to radar data, both components are found to have radiative impacts capable of offsetting biases caused by cloud misrepresentation. Part II of this paper implements Tripleclouds and exponential-random overlap into a radiation code and examines both their individual and combined impacts on the global radiation budget using re-analysis data.

Effect of improving representation of horizontal and vertical cloud structure on the Earth's global radiation budget. Part II: The global effects

Reliably representing both horizontal cloud inhomogeneity and vertical cloud overlap is fundamentally important for the radiation budget of a general circulation model. Here, we build on the work of Part One of this two-part paper by applying a pair of parameterisations that account for horizontal inhomogeneity and vertical overlap to global re-analysis data. These are applied both together and separately in an attempt to quantify the effects of poor representation of the two components on radiation budget. Horizontal inhomogeneity is accounted for using the “Tripleclouds” scheme, which uses two regions of cloud in each layer of a gridbox as opposed to one; vertical overlap is accounted for using “exponential-random” overlap, which aligns vertically continuous cloud according to a decorrelation height. These are applied to a sample of scenes from a year of ERA-40 data. The largest radiative effect of horizontal inhomogeneity is found to be in areas of marine stratocumulus; the effect of vertical overlap is found to be fairly uniform, but with larger individual short-wave and long-wave effects in areas of deep, tropical convection. The combined effect of the two parameterisations is found to reduce the magnitude of the net top-of-atmosphere cloud radiative forcing (CRF) by 2.25 W m−2, with shifts of up to 10 W m−2 in areas of marine stratocumulus. The effects of the uncertainty in our parameterisations on radiation budget is also investigated. It is found that the uncertainty in the impact of horizontal inhomogeneity is of order ±60%, while the uncertainty in the impact of vertical overlap is much smaller. This suggests an insensitivity of the radiation budget to the exact nature of the global decorrelation height distribution derived in Part One.

Thermodynamics of climate change: generalized sensitivities

Using a recent theoretical approach, we study how global warming impacts the thermodynamics of the climate system by performing experiments with a simplified yet Earth-like climate model. The intensity of the Lorenz energy cycle, the Carnot efficiency, the material entropy production, and the degree of irreversibility of the system change monotonically with the CO2 concentration. Moreover, these quantities feature an approximately linear behaviour with respect to the logarithm of the CO2 concentration in a relatively wide range. These generalized sensitivities suggest that the climate becomes less efficient, more irreversible, and features higher entropy production as it becomes warmer, with changes in the latent heat fluxes playing a predominant role. These results may be of help for explaining recent findings obtained with state of the art climate models regarding how increases in CO2 concentration impact the vertical stratification of the tropical and extratropical atmosphere and the position of the storm tracks.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Vertical heat transports in the ocean and their effect on time-dependent climate change

In response to increasing atmospheric con- centrations of greenhouse gases, the rate of time- dependent climate change is determined jointly by the strength of climate feedbacks and the e�ciency of pro- cesses which remove heat from the surface into the deep ocean. This work examines the vertical heat transport processes in the ocean of the HADCM2 atmosphere± ocean general circulation model (AOGCM) in experi- ments with CO2 held constant (control) and increasing at 1% per year (anomaly). The control experiment shows that global average heat exchanges between the upper and lower ocean are dominated by the Southern Ocean, where heat is pumped downwards by the wind- driven circulation and di�uses upwards along sloping isopycnals. This is the reverse of the low-latitude balance used in upwelling±di�usion ocean models, the global average upward di�usive transport being against the temperature gradient. In the anomaly experiment, weakened convection at high latitudes leads to reduced diffusive and convective heat loss from the deep ocean, and hence to net heat uptake, since the advective heat input is less a�ected. Reduction of deep water produc- tion at high latitudes results in reduced upwelling of cold water at low latitudes, giving a further contribution to net heat uptake. On the global average, high-latitude processes thus have a controlling in¯uence. The impor- tant role of di�usion highlights the need to ensure that the schemes employed in AOGCMs give an accurate representation of the relevant sub-grid-scale processes.

Dynamic stall for a Vertical Axis Wind Turbine in a two-dimensional study

The last few years have proved that Vertical Axis Wind Turbines (VAWTs) are more suitable for urban areas than Horizontal Axis Wind Turbines (HAWTs). To date, very little has been published in this area to assess good performance and lifetime of VAWTs either in open or urban areas. At low tip speed ratios (TSRs<5), VAWTs are subjected to a phenomenon called 'dynamic stall'. This can really affect the fatigue life of a VAWT if it is not well understood. The purpose of this paper is to investigate how CFD is able to simulate the dynamic stall for 2-D flow around VAWT blades. During the numerical simulations different turbulence models were used and compared with the data available on the subject. In this numerical analysis the Shear Stress Transport (SST) turbulence model seems to predict the dynamic stall better than the other turbulence models available. The limitations of the study are that the simulations are based on a 2-D case with constant wind and rotational speeds instead of considering a 3-D case with variable wind speeds. This approach was necessary for having a numerical analysis at low computational cost and time. Consequently, in the future it is strongly suggested to develop a more sophisticated model that is a more realistic simulation of a dynamic stall in a three-dimensional VAWT.

Cloud-base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

The statistics of cloud-base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in Central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that, as expected, AROME significantly underestimates the variability of vertical velocity at cloud-base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4-6 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70-80% of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 4 times the physically-defined grid spacing. The results illustrate the need for special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.