The results show that the probability of occurrence of a negative phase surrounded by two positive phases within a 107-year period is approximately 9.9%. The raw data's mean positive phase length is close to the simulation mean and median, while the absolute difference in maximum positive/negative phase lengths corresponds to a p-value of 14.9%. The methodology developed in this paper can be useful to ecologists in assessing the potential ecological effects due to PDO variation, and for estimating the probabilities associated with future phases or other events.

This paper explores wildfire modeling based on meteorological variables for Tanjung Puting National Park, located on the island of Borneo. A separable model is developed for predicting daily wildfire burn area using variables such as temperature, sea level pressure, humidity, precipitation, visibility, and wind speed. Each component in the model is estimated using kernel smoothing and maximum likelihood methods. The data are shown to be largely compatible with the separable model, suggesting that the relationship between wildfire burn area and any of these weather variables in particular does not appear to change significantly depending on the values of the other weather variables. The analysis appears to confirm the findings of previous studies on wildfire in Southern California which indicate that wildfire hazard may be suitably estimated using a simple multiplicative model where the impact of each weather covariate is estimated separately.