Sea level rise adaptation: emerging lessons for local policy development

Many coastal communities across the United States are beginning to plan for climate-related sea level rise. While impacts and solutions will vary with local conditions, jurisdictions which have begun this process seem to pass through three common stages when developing policy for local sea level rise adaptation: l) building awareness about local sea level rise threats, 2) undertaking analyses of local vulnerabilities, and 3) developing plans and policies to deal with these vulnerabilities. The purpose of this paper is to help advance community dialogue and further inform local decision-makers about key elements and steps for addressing climate-related sea level rise. It summarizes the results of a project the Marine Policy Institute (MPI) undertook during 2011-12 to review experiences from fourteen U.S. coastal jurisdictions representing a variety of city, county, and state efforts with sea level adaptation. There are many more initiatives underway than those reflected in this sample, but the “focus jurisdictions” were selected because of the extensive information publically available on their experiences and lessons being learned that could provide insights for coastal communities, especially in Southwest Florida

Five-Loop Static Contribution to the Gravitational Interaction Potential of Two Point Masses

We compute the static contribution to the gravitational interaction potential of two point masses in the velocity-independent five-loop (and 5th post-Newtonian) approximation to the harmonic coordinates effective action in a direct calculation. The computation is performed using effective field methods based on Feynman diagrams in momentum-space in $d = 3 - 2\varepsilon$ space dimensions. We also reproduce the previous results including the 4th post-Newtonian order.Comment: 15 pages, 4 figure

Neutron scattering as a probe of the Fe-pnicitide superconducting gap

Inelastic neutron scattering provides a probe for studying the spin and momentum structure of the superconducting gap. Here, using a two-orbital model for the Fe-pnicitide superconductors and an RPA-BCS approximation for the dynamic spin susceptibility, we explore the scattering response for various gaps that have been proposed.Comment: 5 pages, 4 figure

Forecasting economic growth in the euro area during the Great Moderation and the Great Recession

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus data from national economies (pseudo-real time data). We estimate backcasts, nowcasts and forecasts for GDP, components of GDP, and GDP of all individual euro area members, and examine forecasts for periods of low and high economic volatility (more specifically, we consider 2002-2007, which falls into the ‘Great Moderation’, and the ‘Great Recession’ 2008-2009). We find that all models consistently beat naive AR benchmarks, and overall, the dynamic factor model tends to outperform the PMI model (at times by a wide margin). However, accuracy of the dynamic factor model can be uneven (forecasts for some countries have large errors), with the PMI model dominating clearly for some countries or over some horizons. This is particularly pronounced over the Great Recession, where the dynamic factor model dominates the PMI model for backcasts, but has considerable difficulties beating the PMI model for nowcasts. This suggests that survey-based measures can have considerable advantages in responding to changes during very volatile periods, whereas factor models tend to be more sluggish to adjust. JEL Classification: C50, C53, E37, E47dynamic factor model, forecasting, PMI model

Model granularity and related concepts

Models are integral to engineering design and basis for many decisions. Therefore, it is necessary to comprehend how a model’s properties might influence its behaviour. Model granularity is an important property but has so far only received limited attention. The terminology used to describe granularity and related phenomena varies and pertinent concepts are distributed across communities. This article positions granularity in the theoretical background of models, collects formal definitions for relevant terms from a range of communities and discusses the implications for engineering design

Evolution of the neutron resonances in AFe2Se2

Recent experiments on the alkali-intercalated iron selenides have raised questions about the symmetry of the superconducting phase. Random phase approximation calculations of the leading pairing eigenstate for a tight- binding 5-orbital Hubbard-Hund model of AFe2Se2 find that a d-wave (B1g) state evolves into an extended s{\pm} (A1g) state as the system is hole-doped. However, over a range of doping these two states are nearly degenerate. Here, we calculate the imaginary part of the magnetic spin susceptibility \chi"(q,{\omega}) for these gaps and discuss how the evolution of neutron scattering resonances can distinguish between them

‘Lean’ versus ‘Rich’ Data Sets: Forecasting during the Great Moderation and the Great Recession

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus data from national economies (pseudo-real time data). We estimate backcasts, nowcasts and forecasts for GDP, components of GDP, and GDP of all individual euro area members, and examine forecasts for the ‘Great Moderation’ (2000-2007) and the ‘Great Recession’ (2008-2009) separately. All models consistently beat naïve AR benchmarks. More data does not necessarily improve forecasting accuracy: For the factor model, adding monthly indicators from national economies can lead to more uneven forecasting accuracy, notably when forecasting components of euro area GDP during the Great Recession. This suggests that the merits of national data may reside in better estimation of heterogeneity across GDP components, rather than in improving headline GDP forecasts for individual euro area countries. Comparing factor models to the much simpler PMI model, we find that the dynamic factor model dominates the latter during the Great Moderation. However, during the Great Recession, the PMI model has the advantage that survey-based measures respond faster to changes in the outlook, whereas factor models are more sluggish in adjusting. Consequently, the dynamic factor model has relatively more difficulties beating the PMI model, with relatively large errors in forecasting some countries or components of euro area GDP.Econometric and statistical methods; International topics

Systematic analysis of a spin-susceptibility representation of the pairing interaction in the 2D Hubbard model

A dynamic cluster quantum Monte Carlo algorithm is used to study a spin susceptibility representation of the pairing interaction for the two-dimensional Hubbard model with an on-site Coulomb interaction equal to the bandwidth for various doping levels. We find that the pairing interaction is well approximated by {3/2}\Ub(T)^2\chi(K-K') with an effective temperature and doping dependent coupling \Ub(T) and the numerically calculated spin susceptibility $\chi(K-K')$. We show that at low temperatures, \Ub may be accurately determined from a corresponding spin susceptibility based calculation of the single-particle self-energy. We conclude that the strength of the d-wave pairing interaction, characterized by the mean-field transition temperature, can be determined from a knowledge of the dressed spin susceptibility and the nodal quasiparticle spectral weight. This has important implications with respect to the questions of whether spin fluctuations are responsible for pairing in the high-T$_c$ cuprates.Comment: 5 pages, 5 figure