The article introduces a dataset called the Climate Physical Risk Index (CPRI) that measures global climate physical risks. The dataset, constructed by researchers from various institutions in China, covers 170 countries and focuses on four extreme climate events: extreme low temperature (LTD), extreme high temperature (HTD), extreme rainfall (ERD), and extreme drought (EDD). The CPRI dataset is based on daily meteorological observations from 1973 to 2023, with historical data used to set thresholds for extreme values. The dataset includes sub-indices for each extreme event and a comprehensive index for overall climate physical risk. The indices are standardized using min-max normalization and then averaged to create the CPRI. The dataset is available for regular updates and can be extended to sub-national or regional levels upon request. The authors acknowledge the limitations, such as the assumption of equal importance of meteorological stations and the availability of data in smaller regions. The work is supported by the National Natural Science Foundation of China.The article introduces a dataset called the Climate Physical Risk Index (CPRI) that measures global climate physical risks. The dataset, constructed by researchers from various institutions in China, covers 170 countries and focuses on four extreme climate events: extreme low temperature (LTD), extreme high temperature (HTD), extreme rainfall (ERD), and extreme drought (EDD). The CPRI dataset is based on daily meteorological observations from 1973 to 2023, with historical data used to set thresholds for extreme values. The dataset includes sub-indices for each extreme event and a comprehensive index for overall climate physical risk. The indices are standardized using min-max normalization and then averaged to create the CPRI. The dataset is available for regular updates and can be extended to sub-national or regional levels upon request. The authors acknowledge the limitations, such as the assumption of equal importance of meteorological stations and the availability of data in smaller regions. The work is supported by the National Natural Science Foundation of China.