Multi-satellite observed responses of precipitation and its extremes to interannual climate variability

The consistency of precipitation variability estimated from the multiple satellite-based observing systems is assessed. There is generally good agreement between TRMM TMI, SSM/I, GPCP and AMSRE datasets for the inter-annual variability of precipitation since 1997 but the HOAPS dataset appears to overestimate the magnitude of variability. Over the tropical ocean the TRMM 3B42 dataset produces unrealistic variabilitys. Based upon deseasonalised GPCP data for the period 1998-2008, the sensitivity of global mean precipitation (P) to surface temperature (T) changes (dP/dT) is about 6%/K, although a smaller sensitivity of 3.6%/K is found using monthly GPCP data over the longer period 1989-2008. Over the tropical oceans dP/dT ranges from 10-30%/K depending upon time-period and dataset while over tropical land dP/dT is -8 to -11%/K for the 1998-2008 period. Analyzing the response of the tropical ocean precipitation intensity distribution to changes in T we find the wetter area P shows a strong positive response to T of around 20%/K. The response over the drier tropical regimes is less coherent and varies with datasets, but responses over the tropical land show significant negative relationships over an interannual time-scale. The spatial and temporal resolutions of the datasets strongly influence the precipitation responses over the tropical oceans and help explain some of the discrepancy between different datasets. Consistency between datasets is found to increase on averaging from daily to 5-day time-scales and considering a 1o (or coarser) spatial resolution. Defining the wet and dry tropical ocean regime by the 60th percentile of P intensity, the 5-day average, 1o TMI data exhibits a coherent drying of the dry regime at the rate of -20%/K and the wet regime becomes wetter at a similar rate with warming.

Steering across scales: applying Strategic-Relational Approach to a study of land mobilisation for road widening in Kochi

This paper argues for the relevance of paying attention to structuring participation processes across scales as one of the ways in which participation of multi-organisational partnerships that involve conflicting interests might be managed. Issue wise the paper deals with problems in connection with land mobilisation for road widening in complex and concentrated high value urban settings. It discusses a case study of plan implementation involving individual landowners, the land development market, the local government, other governmental and non-governmental organisations and the state government, which together achieved objectives that seemed impossible at first sight. In theoretical terms, the paper engages with Jessop's (2001) Strategic-Relational Approach (SRA), arguing for its potential for informing action in a way that is capable of achieving steering outputs. The claim for SRA is demonstrated by re-examining the case study. The factors that come through as SRA is applied are drawn out and it is suggested that the theory though non-deterministic, helps guide action by highlighting certain dynamics of systems that can be used for institutional intervention. These dynamics point to the importance of paying attention to scale and the way in which participation and negotiation processes are structured so as to favour certain outcomes rather than others

Policy ‘framing’ and evidence-based planning: ‘epistemic communities’ in the multi-jurisdictional environment of an enlarged Europe

The following paper builds on ongoing discussions over the spatial and territorial turns in planning, as it relates to the dynamics of evidence-based planning and knowledge production in the policy process. It brings this knowledge perspective to the organizational and institutional dynamics of transformational challenges implicit in the recent enlargement of the EU. Thus it explores the development of new spatial ideas and planning approaches, and their potential to shape or ‘frame’ spatial policy through the formulation of new institutional arrangements and the de-institutionalization of others. That is, how knowledge is created, contested, mobilized and controlled across governance architectures or territorial knowledge channels. In so doing, the paper elaborates and discusses a theoretical framework through which the interplay of knowledge and policymaking can be conceptualized and analyzed.

Sub-agent elements for control methods in multi-agent energy management system

Increased penetration of generation and decentralised control are considered to be feasible and effective solution for reducing cost and emissions and hence efficiency associated with power generation and distribution. Distributed generation in combination with the multi-agent technology are perfect candidates for this solution. Pro-active and autonomous nature of multi-agent systems can provide an effective platform for decentralised control whilst improving reliability and flexibility of the grid.

Aligning business and IT from multi-level learning perspectives

Business and IT alignment is increasingly acknowledged as a key for organisational performance. However, alignment research lack to mechanisms that enable for on-going process with multi-level effects. Multi-level learning allows on-going effectiveness through development of the organisation and improved quality of business and IT strategies. In particular, exploration and exploitation enable effective process of alignment across dynamic multi-level of learning. Hence, this paper proposes a conceptual framework that links multi-level learning and business-IT strategy through the concept of exploration and exploitation, which considers short-term and long-term alignment together to address the challenges of strategic alignment faced in sustaining organisational performance.

Multi-target out-of-sequence data association

In data fusion systems, one often encounters measurements of past target locations and then wishes to deduce where the targets are currently located. Recent research on the processing of such out-of-sequence data has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships between the algorithms so that any approximations made are explicit.