A comparative sensitivity analysis of human thermal comfort indices with generalized additive models

Investigating the Behaviour of Human Thermal Indices under Divergent Atmospheric Conditions: A Sensitivity Analysis Approach

“…In addition, and while critical studies pertaining to climatic indices were disseminated before the turn of the century [1][2][3][4][5][6][7][8][9][10][11][12][13], since the ingress into the twenty-first century (and arguably further instigated by the arrival of the climate change adaptation agenda), the importance and development of climatic indices have increased. In accordance with the rational presented by Potchter et al [14], the associated research complexity intrinsic to climatic models can be seen under two prisms, the: (i) overall review, cataloguing, structuring, and fragmentation of index typologies based upon their equational suitability and methodical pertinence [15][16][17][18][19][20]; and, (ii) the pursuit and testing of the most suitable index to estimate thermal comfort thresholds within a specific outdoor and climatic setting [21][22][23][24][25][26][27][28]. Both of these perspectives indicate the significance and opportunities regarding the correct approach to human thermal comfort thresholds within urban environments.…”

“…The major drawback of the 'moving one factor' direct methods is that the examined combinations of input parameters' values are very few, and in most cases, are fictional. On the other hand, if one has to examine the impact of the measured inputs' values variation to the model's output values, the cases are finite [27]. As suggested by Ferretti et al [97], moving one factor at a time away from a fixed baseline in a multidimensional space of uncertain factors renders most of that resulting space unexplored.…”

“…Nevertheless, many investigations have reported that numerical experiments do not include design at all. For this specific study, it was chosen to use large data sets with high amounts of real measurements to avoid the aforementioned uncertainties [27,98].…”

“…However, for outdoor work and from a recreational point of view, it is the combined effect of the variables which is of interest" (p.58). As a result, this research was conducted through the implementation of a methodology able to reveal the impact of an input parameter on the climatic index's sensitivity under real atmospheric conditions, as established by Charalampopoulos [27]. Similar to this recent study, GAMs were also correspondingly utilised as a means to analyse the sensitivity patterns of the same predetermined climatic indices on their major input's variation.…”

“…More specifically, through the utilisation of Generalised Additive Models (GAMs), the sensitivity behaviour of six selected thermal comfort indices was investigated while accounting for major input variations under different classes of Wind Speed (WS) and air temperature (T a ) conditions. The disclosed sensitivity analysis further develops the methodology undertaken by Charalampopoulos [27], who launched the inaugural step in confirming the applicability of GAMs to identify the sensitivity of numerous climatic indices using high temporal resolution datasets. In this particular study, GAMs are once again utilised to approach large, yet chaotic datasets, with the aim of pinpointing the sensitivity variations between that of algebraic/statistical models against energy balance model indices under different meteorological conditions.…”