Difference analysis of accumulated degree-day samples in different regions of China - Weihao Zhu; Xiandun Zhai; Mengzi Yang; Maosheng Qian; Zhenhui Zhang; Yaonan Mo (Wolters Kluwer Medknow Publications, 2021)
Background: Accumulated degree-days (ADD) refers to the temperature value and time within a certain period. More and more attention has been paid to the ADD in the study of postmortem interval (PMI) estimation. Aim and Objective: This study is to confirm whether ADD is applicable in China. Materials and Methods: We collected meteorological data of 10 different regions in China for 12 months, analyzed the distribution characteristics of ADD in different regions at different time periods, and tested the two ADD calculation methods (accumulated hourly temperature and accumulated daily average temperature), in an attempt to establish a more precise calculation method of ADD. Results: The results show that when the yearly or monthly effective temperature data is taken as the research object, the law of daily ADD mean value gradually decreases from south to north, and the average value of accumulated hourly temperature at each region is larger than the average value of accumulated daily average temperature (the difference was significant). In addition, in different periods of each day, ADD obtained at different regions is different, and the variation of its specific gravity also has a north-south difference. We take the daily average temperature as the independent variable and accumulated hourly temperature as the linear equation fitted by the dependent variable, showing a good linear relationship (0.992 ≤ R2 ≤ 0.999). At the same time, we also identify that extra caution should be exercised when using ADD in some special regions (such as Lhasa) or during the cold season of some regions. It may be unrealistic to attempt divide daily ADD into equal parts and accurately estimate PMI to a certain hour on the day of the crime. However, accurate estimation of PMI can be improved by dividing ADD on the day of the crime according to proportion of different periods and checking the time period of the final ADD value. Conclusion: At present, the study results on ADD need to be further developed. our study provides a preliminary research basis for the future establishment of an unified, simple, accurate, and suitable for the ADD model in China.