R is an open-source programming language which gained a central place in the geosciences over the last two decades as the primary tool for research. Now, biometeorological research is driven by the diverse datasets related to the atmosphere and other biological agents (e.g., plants, animals and human beings) and the wide variety of software to handle and analyse them. The demand of the scientific community for the automation of analysis processes, data cleaning, results sharing, reproducibility and the capacity to handle big data brings a scripting language such as R in the foreground of the academic universe. This paper presents the advantages and the benefits of the R language for biometeorological and other atmospheric sciences’ research, providing an overview of its typical workflow. Moreover, we briefly present a group of useful and popular packages for biometeorological research and a road map for further scientific collaboration on the R basis. This paper could be a short introductory guide to the world of the R language for biometeorologists

This paper aims to analyse and conclude about the behaviour of the most commonly used human thermal comfort indices under a variety of atmospheric conditions in order to provide further information about their appropriateness. Utilising Generalized Additive Models (GAMs), this article examines the indices’ sensitivity when exposed to diverse classified atmospheric conditions. Concentrated upon analysing commonly used human thermal indices, two Statistical/Algebraic indices (Thermohygrometric Index (THI) and HUMIDEX (HUM)), and four Energy Balance Model indices (Physiologically Equivalent Temperature (PET), modified PET (mPET), Universal Thermal Climate Index (UTCI), and Perceived Temperature (PT)) were selected. The results of the study are twofold, the identification of (1) index sensitivity to parameters’ variation, and change rates, resultant of different atmospheric conditions; and, (2) the overall pertinence of each of the indices for local thermal comfort evaluation. The results indicate that the thermohygrometric indices cannot follow and present the thermal conditions’ variations. On the other hand, UTCI is very sensitive under low radiation condition, and PET/mPET present higher sensitivity when the weather is dominated by high radiation and air temperature. PT index provides the lower sensitive among the human energy balance indices, but this is adequately sensitive to describe the thermal comfort environment.

This is a sensitivity analysis of the main human thermal comfort indices with Generalized Additive Models

This is an attempt to utilize natural color images derived by drones in order to calculate SVF in a wide and continuous area

A new methodology for the evaluation of bioclimatic performance of open spaces

This paper is an implementation of first derivatives and violin plots for the assessment of urban configuraions on the biometeorological regime

This paper is an estimation of the biometeorological impact of varius urban configurations on the human thermal comfort