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We present a Python package, pwv_kpno, that provides models for theatmospheric transmission due to precipitable water vapor (PWV) at userspecified sites. Using the package, ground-based photometric observations takenbetween $3,000$ and $12,000$ $\AA$ can be corrected for atmospheric effects dueto PWV. Atmospheric transmission in the optical and near-infrared is highlydependent on the PWV column density along the line of sight. By measuring thedelay of dual-band GPS signals through the atmosphere, the SuomiNet projectprovides accurate PWV measurements for hundreds of locations around the world.The pwv_kpno package uses published SuomiNet data in conjunction with MODTRANmodels to determine the modeled, time-dependent atmospheric transmission. Adual-band GPS system was installed at Kitt Peak National Observatory (KPNO) inthe spring of 2015. Using measurements from this receiver we demonstrate thatwe can successfully predict the PWV at KPNO from nearby dual-band GPS stationson the surrounding desert floor. The pwv_kpno package can thus provideatmospheric transmission functions for observations taken before the KPNOreceiver was installed. Using PWV measurements from the desert floor, wecorrectly model PWV absorption features present in spectra taken at KPNO. Wealso demonstrate how to configure the package for use at other observatories.

pwv_kpno: A Python Package for Modeling the Atmospheric Transmission Function due to Precipitable Water Vapor