Assessment of climate classification methodologies used in building energy efficiency sector.

[Display omitted] • The paper reviews 43 articles defining methodologies for climate classification. • The paper provides overview of climate classification and validation methods. • Need of standard methodology or nomenclature for climate classification. • The optimal approach for conducting climate zoning remains a topic of debate. Climate classification simplifies the representation of expected climate conditions by eliminating the need to describe each climatic parameter. Climate classification is frequently used as a basis for recommendations through codes and standards for buildings because a given climate has nearly similar design conditions. Furthermore, building energy efficiency programmes are designed based on the climatic classification to determine appropriate design strategies to eliminate the under-design or over-design of buildings for similar climatic regions. This necessitates the use of realistic and reliable climate classifications. Over the past two decades, numerous research studies have proposed climate classification methods. However, there is a lack of universal acceptance of climate classification methodology to balance complexity and accuracy. This research provides an overview of various climate classification methods and indicators used to assess the significance of climatic conditions. Moreover, this study highlights pressing issues, proposes a feasible climate classification methodology, and offers substantial possibilities for future study. This study organizes and evaluates the various classification and validation methods used by researchers, variables, and the granularity of data used for the classification. The usual criteria for defining a climate are temperature, relative humidity, cooling-degree days, heating-degree days, and solar radiation. About eighty-five percent of the classified climates are using at most three variables. The number and characteristics of climate zones vary with changes in the resolution of climate data, classification methods, and the inclusion of different sets of parameters. Clustering methods are becoming more important for climate classification as these methods can handle multiple variables more accurately. To tackle the complex relationship between climate and building thermal design, it is recommended to use climate variables with cluster analysis and validation based on thermal loads. This paper will give researchers an aerial perspective of the scope and direction of ongoing research in this field. [ABSTRACT FROM AUTHOR]