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The paper proposes a low carbon domestic design framework for sustainable homes in Saudi Arabia, characterized by a rigorous climate and unique regional socio-cultural features. This is informed by (a) an in-depth investigation of the Saudi domestic building stock, including landscaping, massing, space layout, building fabric, on-site renewable potential, and occupants’ lifestyles; and (b) a consultation with 40 experts across Saudi Arabia. The consultation was carried out using the Delphi Technique in multiple rounds. The established framework factors in architectural design strategies, building envelope design, and on-site renewable energy strategies for Saudi Arabia, taking into account socio-cultural considerations. A consensus between the consulted experts was achieved. The proposed framework is applicable and suitable for Saudi Arabia and beyond, including the Middle Eastern region. [ABSTRACT FROM AUTHOR]

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region. [ABSTRACT FROM AUTHOR]