Optical turbulence forecast in the Adaptive Optics realm

(35-words maximum) In this talk I present the scientific drivers related to the optical turbulence forecast applied to the ground-based astronomy supported by Adaptive Optics, the state of the art of the achieved results and the most relevant challenges for future progresses.Comment: 1 figure, Orlando, Florida United States, 25 - 28 June 2018, ISBN: 978-1-943580-44-6,Turbulence & Propagation, JW5I.1 Adaptive Optics: Analysis, Methods and System

"Edible" urban forests as part of inclusive, sustainable cities

Feeding an increasingly urban population and ensuring the economic and social well-being of urban dwellers will be the primary challenge for cities in coming decades. The impacts of climate change are expected to slow down urban economic growth, exacerbate environmental degradation, increase poverty and erode urban food security. Many cities are on a quest for more sustainable urbanization pathways that will enable effective responses to the increasing socio-economic and environmental challenges they face. In the search to \u201cmake cities and human settlements inclusive, safe, resilient and sustainable\u201d (Sustainable Development Goal 11 in the United Nations Sustainable Development Agenda 2030), interest is increasing in growing local food. Edible green infrastructure, mainly in the form of urban food forests and trees (referred to here generally as urban food forests and also sometimes as tree-based edible landscaping), can help address a range of problems caused by rapid and unplanned urbanization, such as food scarcity, poverty, the deterioration of human health and well-being, air pollution, and biodiversity loss. The use of edible plants in urban and peri-urban forestry varies among cities and is influenced by historical, cultural and socio-economic factors. Overall, it has tended to be neglected in modern cities. This article explores the potential of urban and peri-urban forests as sources of food and the role that urban food forests can play in fostering sustainable cities

Edible urban forests as part of inclusive, sustainable cities

Feeding an increasingly urban population and ensuring the economic and social well-being of urban dwellers will be the primary challenge for cities in coming decades. The impacts of climate change are expected to slow down urban economic growth, exacerbate environmental degradation, increase poverty and erode urban food security. Many cities are on a quest for more sustainable urbanization pathways that will enable effective responses to the increasing socio-economic and environmental challenges they face. In the search to “make cities and human settlements inclusive, safe, resilient and sustainable” (Sustainable Development Goal 11 in the United Nations Sustainable Development Agenda 2030), interest is increasing in growing local food. Edible green infrastructure, mainly in the form of urban food forests and trees (referred to here generally as urban food forests and also sometimes as tree-based edible landscaping), can help address a range of problems caused by rapid and unplanned urbanization, such as food scarcity, poverty, the deterioration of human health and well-being, air pollution, and biodiversity loss (FAO, 2016).info:eu-repo/semantics/publishedVersio

Forecasting surface-layer atmospheric parameters at the Large Binocular Telescope site

In this paper, we quantify the performance of an automated weather forecast system implemented on the Large Binocular Telescope (LBT) site at Mt Graham (Arizona) in forecasting the main atmospheric parameters close to the ground. The system employs a mesoscale non-hydrostatic numerical model (Meso-Nh). To validate the model, we compare the forecasts of wind speed, wind direction, temperature and relative humidity close to the ground with the respective values measured by instrumentation installed on the telescope dome. The study is performed over a large sample of nights uniformly distributed over 2 yr. The quantitative analysis is done using classical statistical operators [bias, root-mean-square error (RMSE) and σ] and contingency tables, which allows us to extract complementary key information, such as the percentage of correct detections (PC) and the probability of obtaining a correct detection within a defined interval of values (POD). The results of our study indicate that the model performance in forecasting the atmospheric parameters we have just cited are very good, in some cases excellent: RMSE for temperature is below 1°C, for relative humidity it is 14 per cent and for the wind speed it is around 2.5 m s-1. The relative error of the RMSE for wind direction varies from 9 to 17 per cent depending on the wind speed conditions. This work is performed in the context of the ALTA (Advanced LBT Turbulence and Atmosphere) Center project, whose final goal is to provide forecasts of all the atmospheric parameters and the optical turbulence to support LBT observations, adaptive optics facilities and interferometric facilities

Forecasts of the atmospherical parameters close to the ground at the LBT site in the context of the ALTA project

In this paper we study the abilities of an atmospherical mesoscale model in forecasting the classical atmospherical parameters relevant for astronomical applications at the surface layer (wind speed, wind direction, temperature, relative humidity) on the Large Binocular Telescope (LBT) site - Mount Graham, Arizona. The study is carried out in the framework of the ALTA project aiming at implementing an automated system for the forecasts of atmospherical parameters (Meso-Nh code) and the optical turbulence (Astro-Meso-Nh code) for the service-mode operation of the LBT. The final goal of such an operational tool is to provide predictions with high time frequency of atmospheric and optical parameters for an optimized planning of the telescope operation (dome thermalization, wind-dependent dome orientation, observation planning based on predicted seeing, adaptive optics optimization, etc...). Numerical simulations are carried out with the Meso-Nh and Astro-Meso-Nh codes, which were proven to give excellent results in previous studies focused on the two ESO sites of Cerro Paranal and Cerro Armazones (MOSE Project). In this paper we will focus our attention on the comparison of atmospherical parameters forescasted by the model close to the ground with measurements taken by the observatory instrumentations and stored in the LBT telemetry in order to validate the numerical predictions. As previously done for Cerro Paranal (Lascaux et al., 2015), we will also present an analysis of the model performances based on the method of the contingency tables, that allows us to provide complementary key information with the respect to the bias and RMSE (systematic and statistical errors), such as the percentage of correct detection and the probability to obtain a correct detection inside a defined interval of values