**1. Introduction**

The concept of Climate-Based Daylight Modelling (CBDM) was introduced around 20 years ago by two seminal papers [1,2] that defined it as the prediction of any luminous quantity—mainly illuminance time series on a grid of ideal horizontal sensors—by considering the intrinsic variability of the sun and sky conditions as derived from standard weather data.

According to this approach, the use of hourly—or even finer—time steps to describe the relevant climate variables, as recorded by meteorological stations spread throughout the globe, allows for understanding the daylight distribution in a space under different climates and times of the year. This has the potential to revolutionize the way that daylight is conceived and assessed by practitioners and building scientists, while also questioning the reliability of the traditional approach that is based on the use of the Daylight Factor (*DF*) (or its spatial average *aDF* [3]), as prescribed by many regulatory bodies. It does not appear fortuitous then that very recently the Leadership in Energy and Environmental Design (LEED) rating system introduced the use of two dynamic metrics, such as the spatial Daylight Autonomy (*sDA*) and the Annual Sunlight Exposure (*ASE*), for compliance purposes (Illuminating Engineering Society, LM-83 [4]), thus replacing the option of running simulations under fixed clear sky conditions. Furthermore, in 2013, the Education Funding Agency in the United Kingdom (UK) was the first public organization that made mandatory the use of the Useful Daylight Illuminance

(*UDI*) metrics [5] for the evaluation of design proposals that were submitted to the Priority Schools Building Programme [6].

However, despite the indisputable advances achieved by considering real (i.e., recorded) time series of irradiance/illuminance values from largely available weather datasets, there are some concerns to bear in mind when adopting CBDM.

First, the choice of the weather dataset should be based on the purposes of the modelling and the underlying characteristics of the dataset itself (e.g., location, measurement period, statistical techniques being employed for resembling typical or extreme weather conditions). In fact, as demonstrated by Bellia et al. [7], using the IWEC (International Weather for Energy Calculation), Meteonorm, Satel-Light, or TRY weather sources could lead to different results in terms of Annual Light Exposures (i.e., the amount of light falling onto a certain point throughout the year, measured in luxh), and of various dynamic metrics, such as the Daylight Availability (*DA*, [8]) and the *UDI*. This happens because usually the TRY datasets show lower values for the global horizontal irradiance than in other sources; however, these outcomes were only proven for a north-oriented room, while different exposures could lead to different results because of sunlight contribution [7].

Secondly, there is a lack of consensus around the choice of the metrics and of their thresholds to judge if a space is 'well daylit' or not. The variety of CBDM approaches employed for educational buildings, ranging from traditional illuminance and luminance distribution under fixed sky conditions to novel circadian metrics, has been documented in a recent review paper by Costanzo et al. [9].

As an example, in regards to the above-mentioned adoption of the *UDI* metrics for school buildings design in the UK, Littlefair noted that the way calculations are conducted, in terms of offset distance from the walls, grid size, operational hours, and threshold values, might affect the outcomes [10]. This does not allow for comparison among spaces that are used for different purposes (e.g., schools, offices, houses).

Does it mean we should neglect the advances in daylight modelling, and stick to the current 50 years old practice? According to Tregenza [11], the daylight factor would still play a role in daylighting mandatory standards when a simple, robust, meaningful, and easy to test metrics is required for compliance with building codes, provided that a mandatory standard is the best option to achieve a good design. Nonetheless, the same author stated that CBDM should be used creatively, to explore new design solutions driven by different space requirements, orientations, and climate conditions.

Mardaljevic has critically assessed all of these aspects during a recent CIBSE technical symposium [12], demonstrating that, apart from a (quite) understandable 'shock of the new' for everyone that is involved in the fields of daylighting and lighting design, some of the critics are neither well-founded nor would automatically assign a preference to the old practice based on static illuminance ratios.

For example, the care in choosing the 'right' weather file is commonly accepted for thermal simulations, where, except for specific purposes, such as complying with energy performance certification requirements or peak loads calculations, steady-state methods are already put aside in favour of dynamic ones. It seems then that the daylighting simulation community is just a step away from doing it as well.

Furthermore, there is evidence of overheating and glare issues recorded in buildings designed to comply with the minimum *DF* requirements, whose main rationale was to guarantee a minimum sufficient quantity of light for different visual tasks under the worst conditions of a standard overcast sky [13].

What appears more founded is rather the critique about the somehow subjective and arbitrary threshold values set for some of the CBDM metrics, such as *sDA*, *ASE*, and *UDI* (see the next section for their definition and calculation methods). In this sense, more case studies are needed to prove the concept and show their potentialities of informing on different design solutions when being 'creatively' used.

This paper contributes to advance the familiarity with the use of dynamic daylight simulations by presenting a range of design options fitting the needs of different users of a surveyed elementary school that is located in the Mediterranean climate of Agira (Sicily). The local climatic conditions, mostly sunny throughout the year, indeed require the integration of different shading and re-directing systems with the existing envelope and rooms' layout, a task that has been accomplished by employing several CBDM and static metrics. Results show that the dynamic modelling of the spaces is a powerful tool in the designer's hands, helping to inform about the choice of the most appropriate technological solutions and their architectural integration.
