Estimating crime scene temperatures from nearby meteorological station data.

The importance of temperature data in minimum postmortem interval (min PMI) estimations in criminal investigations is well known. To maximise the accuracy of min PMI estimations, it is imperative to investigate the different components involved in temperature modelling, such as the duration of temperature data logger placement at the crime scene and choice of nearest weather station to compare the crime scene data to. Currently, there is no standardised practice on how long to leave the temperature data logger at the crime scene and the effects of varying logger duration are little known. The choice of the nearest weather station is usually made based on availability and accessibility of data from weather stations in the crime scene vicinity. However, there are no guidelines on what to look for to maximise the comparability of weather station and crime scene temperatures. Linear regression analysis of scene data with data from weather stations with varying time intervals, distances, altitudes and microclimates showed the greatest goodness of fit (R2 ), i.e. the highest compatibility between datasets, after 4-10 days. However, there was no significant improvement in estimation of crime scene temperatures beyond a 5-day regression period. The smaller the distance between scene and weather station and the higher the similarity in environment, such as altitude and geographical area, resulted in greater compatibility between datasets. Overall, the study demonstrated the complexity of choosing the most comparable weather station to the crime scene, especially because of a high variation in seasonal temperature and numerous influencing factors such as geographical location, urban 'heat island effect' and microclimates. Despite subtle differences, for both urban and rural areas an optimal data fit was generally reached after about five consecutive days within a radius of up to 30 km of the 'crime scene'. With increasing distance and differing altitudes, a lower overall data fit was observed, and a diminishing increase in R2 values was reached after 4-10 consecutive days. These results demonstrate the need for caution regarding distances and climate differences when using weather station data for retrospective regression analyses for estimating temperatures at crime scenes. However, the estimates of scene temperatures from regression analysis were better than simply using the temperatures from the nearest weather station. This study provides recommendations for data logging duration of operation, and a baseline for further research into producing standard guidelines for increasing the accuracy of min PMI estimations and, ultimately, greater robustness of forensic entomology evidence in court.