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Climate threats to coastal infrastructure and sustainable development outcomes
Data availability:
Data used in this study can be accessed at https://doi.org/10.5281/zenodo.10554713.Code availability: Code relevant to the analysis can be accessed at https://www.dropbox.com/scl/fi/tpjcxtl4j9m9ht0tl0ocq/NCLIM-23071599-code_final.zip?rlkey=ux7du7k4rkru352moob6quwwu&dl=0.Change history: 11 March 2024A Correction to this paper has been published: https://doi.org/10.1038/s41558-024-01974-8Acknowledgements: We acknowledge the Bangladesh Climate Change and Disaster Risk Management Team at the World Bank, in particular S. Kazi and I. Urrutia, for providing the synthetic household data and general support throughout the project. Any views expressed are not necessarily those of or endorsed by the World Bank. We also acknowledge support from the United Nations Office for Project Services (UNOPS), the Global Center on Adaptation (GCA), the Government of Bangladesh, and the Center for Environmental and Geographic Information Services (CEGIS) for assisting with access to data and in-country facilitation. We acknowledge imagery courtesy of the United Nations Sustainable Development Goals (https://www.un.org/sustainabledevelopment), although the content of this publication is not endorsed by the United Nations or its officials or the Member States.Climate hazards pose increasing threats to development outcomes across the worldâs coastal regions by impacting infrastructure service delivery. Using a high-resolution dataset of 8.2 million households in Bangladeshâs coastal zone, we assess the extent to which infrastructure service disruptions induced by flood, cyclone and erosion hazards can thwart progress towards the Sustainable Development Goals (SDGs). Results show that climate hazards potentially threaten infrastructure service access to all households, with the poorest being disproportionately threatened in 69% of coastal subdistricts. Targeting adaptation to these climatic threats in one-third (33%) of the most vulnerable areas could help to safeguard 50â85% of achieved progress towards SDG 3, 4, 7, 8 and 13 indicators. These findings illustrate the potential of geospatial climate risk analyses, which incorporate direct household exposure and essential service access. Such high-resolution analyses are becoming feasible even in data-scarce parts of the world, helping decision-makers target and prioritize pro-poor development.Open access funding provided by Royal Institute of Technology
Collapsing lattice animals and lattice trees in two dimensions
We present high statistics simulations of weighted lattice bond animals and
lattice trees on the square lattice, with fugacities for each non-bonded
contact and for each bond between two neighbouring monomers. The simulations
are performed using a newly developed sequential sampling method with
resampling, very similar to the pruned-enriched Rosenbluth method (PERM) used
for linear chain polymers. We determine with high precision the line of second
order transitions from an extended to a collapsed phase in the resulting
2-dimensional phase diagram. This line includes critical bond percolation as a
multicritical point, and we verify that this point divides the line into two
different universality classes. One of them corresponds to the collapse driven
by contacts and includes the collapse of (weakly embeddable) trees, but the
other is {\it not yet} bond driven and does not contain the Derrida-Herrmann
model as special point. Instead it ends at a multicritical point where a
transition line between two collapsed phases (one bond-driven and the other
contact-driven) sparks off. The Derrida-Herrmann model is representative for
the bond driven collapse, which then forms the fourth universality class on the
transition line (collapsing trees, critical percolation, intermediate regime,
and Derrida-Herrmann). We obtain very precise estimates for all critical
exponents for collapsing trees. It is already harder to estimate the critical
exponents for the intermediate regime. Finally, it is very difficult to obtain
with our method good estimates of the critical parameters of the
Derrida-Herrmann universality class. As regards the bond-driven to
contact-driven transition in the collapsed phase, we have some evidence for its
existence and rough location, but no precise estimates of critical exponents.Comment: 11 pages, 16 figures, 1 tabl
Counting Lattice Animals in High Dimensions
We present an implementation of Redelemeier's algorithm for the enumeration
of lattice animals in high dimensional lattices. The implementation is lean and
fast enough to allow us to extend the existing tables of animal counts,
perimeter polynomials and series expansion coefficients in -dimensional
hypercubic lattices for . From the data we compute formulas
for perimeter polynomials for lattice animals of size in arbitrary
dimension . When amended by combinatorial arguments, the new data suffices
to yield explicit formulas for the number of lattice animals of size
and arbitrary . We also use the enumeration data to compute numerical
estimates for growth rates and exponents in high dimensions that agree very
well with Monte Carlo simulations and recent predictions from field theory.Comment: 18 pages, 7 figures, 6 tables; journal versio
Simulations of lattice animals and trees
The scaling behaviour of randomly branched polymers in a good solvent is
studied in two to nine dimensions, using as microscopic models lattice animals
and lattice trees on simple hypercubic lattices. As a stochastic sampling
method we use a biased sequential sampling algorithm with re-sampling, similar
to the pruned-enriched Rosenbluth method (PERM) used extensively for linear
polymers. Essentially we start simulating percolation clusters (either site or
bond), re-weigh them according to the animal (tree) ensemble, and prune or
branch the further growth according to a heuristic fitness function. In
contrast to previous applications of PERM, this fitness function is {\it not}
the weight with which the actual configuration would contribute to the
partition sum, but is closely related to it. We obtain high statistics of
animals with up to several thousand sites in all dimension 2 <= d <= 9. In
addition to the partition sum (number of different animals) we estimate
gyration radii and numbers of perimeter sites. In all dimensions we verify the
Parisi-Sourlas prediction, and we verify all exactly known critical exponents
in dimensions 2, 3, 4, and >= 8. In addition, we present the hitherto most
precise estimates for growth constants in d >= 3. For clusters with one site
attached to an attractive surface, we verify the superuniversality of the
cross-over exponent at the adsorption transition predicted by Janssen and
Lyssy. Finally, we discuss the collapse of animals and trees, arguing that our
present version of the algorithm is also efficient for some of the models
studied in this context, but showing that it is {\it not} very efficient for
the `classical' model for collapsing animals.Comment: 17 pages RevTeX, 29 figures include
Data Management for Large Scale Power Quality Surveys
For large scale power quality surveys, the management of the large amount of data generated is a major issue. This paper presents solutions to three main areas of data management, viz. a data interchange format, database design and data processing. Consideration of these issues has come about as a result of the Long Term National Power Quality Survey currently being conducted by the University of Wollongong, and reference is made to that specific application for illustrative purposes
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