splitr | Use the HYSPLIT model from inside R and do

splitr is a R library. splitr has no bugs, it has no vulnerabilities and it has low support. However splitr has a Non-SPDX License. You can download it from GitHub.

splitr is an R package for conducting trajectory and dispersion modeling with HYSPLIT. We can determine, from one or more receptor sites, where arriving air masses originated. Conversely, it’s possible to model trajectories of air masses from receptor sites. Forward and backward modeling of gas-phase or particulate matter can also be conducted from defined sites. It’s a means to help explain how, where, and when chemicals and materials are atmospherically transported, dispersed, and deposited. This model has many applications. Some have modeled the atmospheric transport of moisture to determine probable extreme rainfall locations leading to flood events (Gustafsson et al., 2010). Similarly, Creamean et al., 2013 have presented a direct link between long-range transported dust and biological aerosols affecting cloud ice formation and precipitation processes in western United States. Others have successfully improved understanding of invasive species dispersal abilities to inform conservation and landscape management (Lander et al., 2014). Along similar lines, the long-distance transport of high-risk plant pathogens can be modeled with HYSPLIT to assist with plant disease management decisions, such as applications of fungicide or pesticide to potentially-affected agricultural areas (Schmale and Ross, 2015). splitr allows you to build and run HYSPLIT models in a fast, easy, and organized manner. A few or, perhaps, thousands of trajectory or dispersion runs can be conducted with minimal code. Because splitr is an R interface to HYSPLIT, we can store output in memory and take advantage of the vast selection of R packages to perform statistical analyses and to generate visualizations. This package furthermore simplifies the process of running HYSPLIT models by automating the retrieval and storage of associated meteorological data files.