Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

Exploiting thermally-reversible chemistry for controlling the crosslinking of polymer networks

High explosives are highly sensitive to accidental detonation by impact, fire, shrapnel and small arms fire. This sensitivity can be reduced by storing the energetic material within a rubbery polymer matrix and are known as plastic bonded explosives (PBX). The current procedure used to manufacture PBX involves mixing the energetic material with a hydroxy-functionalised aliphatic polymer. Upon the addition of an isocyanate crosslinker an immediate polymerisation occurs and thus the rapidly curing mixture must be used to fill the missile or shells, referred to as ‘stores’. This process can lead to poor distribution of the crosslinker resulting in the formation of an inhomogeneously crosslinked matrix and the formation of voids. One solution to this problem involves containing the crosslinker within polyurethane microcapsules that are uniformly dispersed in the explosive-polymer mixture. Upon the application of a stimulus the crosslinker can be released from the microcapsules and the formation of a uniformly crosslinked PBX achieved. Herein is reported the design and synthesis of polyurethane microcapsules that release isocyanate crosslinkers when desired using a thermal stimulus. This has been achieved by exploiting the thermally-reversible nature of oxime-urethane and Diels-Alder adducts that have been incorporated into the shell wall of the microcapsules. An alternative approach to controlling the polymerisation of PBX materials has also been achieved using thermally-reversible blocked isocyanates that regenerate the isocyanate crosslinker when exposed to heat.

Sampling uncertainties in surface radiation budget calculations in RADAGAST

In the Radiative Atmospheric Divergence Using ARM Mobile Facility GERB and AMMA Stations (RADAGAST) project we calculate the divergence of radiative flux across the atmosphere by comparing fluxes measured at each end of an atmospheric column above Niamey, in the African Sahel region. The combination of broadband flux measurements from geostationary orbit and the deployment for over 12 months of a comprehensive suite of active and passive instrumentation at the surface eliminates a number of sampling issues that could otherwise affect divergence calculations of this sort. However, one sampling issue that challenges the project is the fact that the surface flux data are essentially measurements made at a point, while the top-of-atmosphere values are taken over a solid angle that corresponds to an area at the surface of some 2500 km2. Variability of cloud cover and aerosol loading in the atmosphere mean that the downwelling fluxes, even when averaged over a day, will not be an exact match to the area-averaged value over that larger area, although we might expect that it is an unbiased estimate thereof. The heterogeneity of the surface, for example, fixed variations in albedo, further means that there is a likely systematic difference in the corresponding upwelling fluxes. In this paper we characterize and quantify this spatial sampling problem. We bound the root-mean-square error in the downwelling fluxes by exploiting a second set of surface flux measurements from a site that was run in parallel with the main deployment. The differences in the two sets of fluxes lead us to an upper bound to the sampling uncertainty, and their correlation leads to another which is probably optimistic as it requires certain other conditions to be met. For the upwelling fluxes we use data products from a number of satellite instruments to characterize the relevant heterogeneities and so estimate the systematic effects that arise from the flux measurements having to be taken at a single point. The sampling uncertainties vary with the season, being higher during the monsoon period. We find that the sampling errors for the daily average flux are small for the shortwave irradiance, generally less than 5 W m−2, under relatively clear skies, but these increase to about 10 W m−2 during the monsoon. For the upwelling fluxes, again taking daily averages, systematic errors are of order 10 W m−2 as a result of albedo variability. The uncertainty on the longwave component of the surface radiation budget is smaller than that on the shortwave component, in all conditions, but a bias of 4 W m−2 is calculated to exist in the surface leaving longwave flux.

Characterization of mineral surfaces using FIB and TEM: a case study of naturally weathered alkali feldspars

Using a focused ion beam (FIB) instrument, electron-transparent samples (termed foils) have been cut from the naturally weathered surfaces of perthitic alkali feldspars recovered from soils overlying the Shap granite, northwest England. Characterization of these foils by transmission electron microscopy (TEM) has enabled determination of the crystallinity and chemical composition of near-surface regions of the feldspar and an assessment of the influence of intragranular microtextures on the microtopography of grain surfaces and development of etch pits. Damage accompanying implantation of the 30 kV Ga+ ions used for imaging and deposition of protective platinum prior to ion milling creates amorphous layers beneath outer grain surfaces, but can be overcome by coating grains with > 85 nm of gold before FIB work. The sidewalls of the foil and feldspar surrounding original voids are also partially amorphized during later stages of ion milling. No evidence was found for the presence of amorphous or crystalline weathering products or amorphous "leached layers" immediately beneath outer grain surfaces. The absence of a leached layer indicates that chemical weathering of feldspar in the Shap soils is stoichiometric, or if non-stoichiometric, either the layer is too thin to resolve by the TEM techniques used (i.e., <=similar to 2.5 nm) or an insufficient proportion of ions have been leached from near-surface regions so that feldspar crystallinity is maintained. No evidence was found for any difference in the mechanisms of weathering where a microbial filament rests on the feldspar surface. Sub-micrometer-sized steps on the grain surface have formed where subgrains and exsolution lamellae have influenced the propagation of fractures during physical weathering, whereas finer scale corrugations form due to compositional or strain-related differences in dissolution rates of albite platelets and enclosing tweed orthoclase. With progressive weathering, etch pits that initiated at the grain surface extend into grain interiors as etch tubes by exploiting preexisting networks of nanopores that formed during the igneous history of the grain. The combination of FIB and TEM techniques is an especially powerful way of exploring mechanisms of weathering within the "internal zone" beneath outer grain surfaces, but results must be interpreted with caution owing to the ease with which artifacts can be created by the high-energy ion and electron beams used in the preparation and characterization of the foils.

Information servers, present and future

Mainframes, corporate and central servers are becoming information servers. The requirement for more powerful information servers is the best opportunity to exploit the potential of parallelism. ICL recognized the opportunity of the 'knowledge spectrum' namely to convert raw data into information and then into high grade knowledge. Parallel Processing and Data Management Its response to this and to the underlying search problems was to introduce the CAFS retrieval engine. The CAFS product demonstrates that it is possible to move functionality within an established architecture, introduce a different technology mix and exploit parallelism to achieve radically new levels of performance. CAFS also demonstrates the benefit of achieving this transparently behind existing interfaces. ICL is now working with Bull and Siemens to develop the information servers of the future by exploiting new technologies as available. The objective of the joint Esprit II European Declarative System project is to develop a smoothly scalable, highly parallel computer system, EDS. EDS will in the main be an SQL server and an information server. It will support the many data-intensive applications which the companies foresee; it will also support application-intensive and logic-intensive systems.

DTM generation from LIDAR data using skewness balancing

LIght Detection And Ranging (LIDAR) data for terrain and land surveying has contributed to many environmental, engineering and civil applications. However, the analysis of Digital Surface Models (DSMs) from complex LIDAR data is still challenging. Commonly, the first task to investigate LIDAR data point clouds is to separate ground and object points as a preparatory step for further object classification. In this paper, the authors present a novel unsupervised segmentation algorithm-skewness balancing to separate object and ground points efficiently from high resolution LIDAR point clouds by exploiting statistical moments. The results presented in this paper have shown its robustness and its potential for commercial applications.

Generic systolic array for genetic algorithms

The authors present a systolic design for a simple GA mechanism which provides high throughput and unidirectional pipelining by exploiting the inherent parallelism in the genetic operators. The design computes in O(N+G) time steps using O(N2) cells where N is the population size and G is the chromosome length. The area of the device is independent of the chromosome length and so can be easily scaled by replicating the arrays or by employing fine-grain migration. The array is generic in the sense that it does not rely on the fitness function and can be used as an accelerator for any GA application using uniform crossover between pairs of chromosomes. The design can also be used in hybrid systems as an add-on to complement existing designs and methods for fitness function acceleration and island-style population management

Optimal inverter design for an induction machine using resonant frequency matching

The frequency responses of two 50 Hz and one 400 Hz induction machines have been measured experimentally over a frequency range of 1 kHz to 400 kHz. This study has shown that the stator impedances of the machines behave in a similar manner to a parallel resonant circuit, and hence have a resonant point at which the Input impedance of the machine is at a maximum. This maximum impedance point was found experimentally to be as low as 33 kHz, which is well within the switching frequency ranges of modern inverter drives. This paper investigates the possibility of exploiting the maximum impedance point of the machine, by taking it into consideration when designing an inverter, in order to minimize ripple currents due to the switching frequency. Minimization of the ripple currents would reduce torque pulsation and losses, increasing overall performance. A modified machine model was developed to take into account the resonant point, and this model was then simulated with an inverter to demonstrate the possible advantages of matching the inverter switching frequency to the resonant point. Finally, in order to experimentally verify the simulated results, a real inverter with a variable switching frequency was used to drive an induction machine. Experimental results are presented.

Interference and communications among active network applications

This paper focuses on active networks applications and in particular on the possible interactions among these applications. Active networking is a very promising research field which has been developed recently, and which poses several interesting challenges to network designers. A number of proposals for e±cient active network architectures are already to be found in the literature. However, how two or more active network applications may interact has not being investigated so far. In this work, we consider a number of applications that have been designed to exploit the main features of active networks and we discuss what are the main benefits that these applications may derive from them. Then, we introduce some forms of interaction including interference and communications among applications, and identify the components of an active network architecture that are needed to support these forms of interaction. We conclude by presenting a brief example of an active network application exploiting the concept of interaction.

The role of sketches in supporting near-synchronous remote communication in computer supported collaborative design

This paper presents recent research into the functions and value of sketch outputs during computer supported collaborative design. Sketches made primarily exploiting whiteboard technology are shown to support subjects engaged in remote collaborative design, particularly when constructed in ‘nearsynchronous’ communication. The authors define near-synchronous communication and speculate that it is compatible with the reflective and iterative nature of design activity. There appears to be significant similarities between the making of sketches in near-synchronous remote collaborative design and those made on paper in more traditional face-to-face settings With the current increase in the use of computer supported collaborative working (CSCW) in undergraduate and postgraduate design education it is proposed that sketches and sketching can make important contributions to design learning in this context

Implementing a generic systolic array for genetic algorithms

We have designed a highly parallel design for a simple genetic algorithm using a pipeline of systolic arrays. The systolic design provides high throughput and unidirectional pipelining by exploiting the implicit parallelism in the genetic operators. The design is significant because, unlike other hardware genetic algorithms, it is independent of both the fitness function and the particular chromosome length used in a problem. We have designed and simulated a version of the mutation array using Xilinix FPGA tools to investigate the feasibility of hardware implementation. A simple 5-chromosome mutation array occupies 195 CLBs and is capable of performing more than one million mutations per second. I. Introduction Genetic algorithms (GAs) are established search and optimization techniques which have been applied to a range of engineering and applied problems with considerable success [1]. They operate by maintaining a population of trial solutions encoded, using a suitable encoding scheme.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Managing arable weeds for biodiversity

As a result of the recent intensification of crop production, the abundance and diversity of UK arable weeds adapted to cultivated land have declined, with an associated reduction in farmland birds. A number of questions need to be addressed when considering how these declines can be reversed. Firstly, can the delivery of crop production and biodiversity be reconciled by spatially separating cropping from designated wildlife areas? A number of subsidised environmental schemes in the UK take this approach and are focused on establishing vegetation cover on uncropped land. However, because of the lack of regular disturbance in these habitats, they are dominated by perennials and they therefore have limited potential for promoting the recovery of annual weed populations. A number of farmland bird species also rely on the provision of resources in field centres, and it is therefore likely that the recovery of their populations will rely on weed management options targeted at the cropped areas of the field. This raises two further questions. Firstly, is it possible to identify beneficial weed species that are relatively poor competitors with the crop and also have biodiversity value? Secondly, are the tools available to manage these species at acceptable levels while controlling pernicious weeds? A number of approaches are being employed to answer these questions, including predicting yield loss from weed competition models and exploiting herbicide selectivity. The further development of these tools is crucial if farmer opposition to managing weeds in crops is to be overcome. (c) 2007 Society of Chemical Industry.

A novel parallel approach to the likelihood-based estimation of admixture in population genetics

Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.