Food Security in Vietnam during the 1990s: The Empirical Evidence

food security, calorie consumption, Vietnam

Armistice Day

page 13

Wavelet correlations to reveal multiscale coupling in geophysical systems

The interactions between climate and the environment are highly complex. Due to this complexity, process-based models are often preferred to estimate the net magnitude and directionality of interactions in the Earth System. However, these models are based on simplifications of our understanding of nature, thus are unavoidably imperfect. Conversely, observation-based data of climatic and environmental variables are becoming increasingly accessible over large scales due to the progress of space-borne sensing technologies and data-assimilation techniques. Albeit uncertain, these data enable the possibility to start unraveling complex multivariable, multiscale relationships if the appropriate statistical methods are applied. Here, we investigate the potential of the wavelet cross-correlation method as a tool for identifying multiscale interactions, feedback and regime shifts in geophysical systems. The ability of wavelet cross-correlation to resolve the fast and slow components of coupled systems is tested on synthetic data of known directionality, and then applied to observations to study one of the most critical interactions between land and atmosphere: the coupling between soil moisture and near-ground air temperature. Results show that our method is not only able to capture the dynamics of the soil moisture-temperature coupling over a wide range of temporal scales (from days to several months) and climatic regimes (from wet to dry), but also to consistently identify the magnitude and directionality of the coupling. Consequently, wavelet cross-correlations are presented as a promising tool for the study of multiscale interactions, with the potential of being extended to the analysis of causal relationships in the Earth system.Comment: Submitted to Journal of Geophysical Research - Atmospher

First passage time statistics of Brownian motion with purely time dependent drift and diffusion

Systems where resource availability approaches a critical threshold are common to many engineering and scientific applications and often necessitate the estimation of first passage time statistics of a Brownian motion (Bm) driven by time-dependent drift and diffusion coefficients. Modeling such systems requires solving the associated Fokker-Planck equation subject to an absorbing barrier. Transitional probabilities are derived via the method of images, whose applicability to time dependent problems is shown to be limited to state-independent drift and diffusion coefficients that only depend on time and are proportional to each other. First passage time statistics, such as the survival probabilities and first passage time densities are obtained analytically. The analysis includes the study of different functional forms of the time dependent drift and diffusion, including power-law time dependence and different periodic drivers. As a case study of these theoretical results, a stochastic model for water availability from surface runoff in snowmelt dominated regions is presented, where both temperature effects and snow-precipitation input are incorporated

The life of Franklin Knight Lane

A biography of Franklin Knight Lane

Deep learning for inverse problems in remote sensing: super-resolution and SAR despeckling

L'abstract è presente nell'allegato / the abstract is in the attachmen

Creating safety nets through semi-parametric index-based insurance: A simulation for Northern Ghana

In West Africa, farm income is highly exposed to risks from crop failure in the drier, inland areas, and from fluctuations in (world market) prices in the wetter coastal areas. As individuals and even extended families are poorly equipped to deal with these, provision of social safety nets is required Our paper reviews the situation in Ghana and the way in which the new financial instrument of index-based insurance might contribute to better it, focusing on the estimation of a crop indemnification scheme for farmers in Northern Ghana. It recalls that in a poor rural area like Northern Ghana, provision of social safety almost coincides with food security management, and must, therefore, distinguish three basic subtasks: distributing income entitlements (possibly indemnification payments from insurance) to the poor, ensuring collection of taxes (possibly insurance premiums) to fund the arrangement, and assuring delivery of staple goods, such as food to the all households, including the poor. We point out that crop insurance, in any form can at best entitle the poor, and with adequate premiums, become adequately funded, albeit that current experience suggests that farmers tend to be reluctant and to find it difficult to fulfill their obligations. Our main remark is, however, that unless the actual availability of goods is assured, the indemnification from crop insurance will under droughts only cause prices to rise and channel away scarce food from the uninsured to the insured. In short, in poor areas such as Northern Ghana co-ordinated food security management is key, particularly under severe droughts, with crop insurance possibly playing a role in the spheres of entitlement and taxation. Turning to the modalities of crop insurance, we mention the advantages of the index-based approach, which as compared to the individualized contracts of commercial insurance greatly reduces transaction costs by basing the indemnification payments on objectively and easily measurable variables, such as rainfall data collected at weather stations, and world prices of main export goods. Our contribution is an improvement of the indemnification schedules. Rather than specifying a synthetic schedule or estimating is as a parametric form, we estimate it as an optimal indemnification that minimizes farmers' risk of having their income drop below the poverty line, while restricting the indemnification to be an unknown function of index variables on weather and prices. We adapt kernel learning technique to conduct this estimation, so as to ensure that the schedule is self-financing, up to a subsidy. Our application is for Northern Ghana where poverty is highest and farming conditions are most risky. We test the scheme's performance as a social safety net in terms of its capacity to reduce basis risk and alleviate poverty. Although our schedule definitely outperforms the parametric forms, basis risk and associated poverty remain considerable.Risk and Uncertainty,

Should I stay or should I go

Rapid migration flows into urban and peri-urban areas will be an on-going driver of the economic transformation that drives Ghana’s economy forward. Recognising this, policies that support better management of urbanisation will have to ensure improved services, transportation, and housing for growing urban populations