The data in the CSV file named RSF is a detailed dataset used to run the models testing relationships between movement behavior and atmospheric conditions. This dataset includes: detection date and rounded hour, status (0 or 1) showing if over-water movement occurring within nine hours was detected, number of hours since sunset, site ID of area weather station, Motus tag ID, wind speed , Temperature, precipitation, visibility, wind direction, the longitudinal component of wind speed and direction, the latitudinal component of wind speed and direction, pressure, wind speed of previous hour, temperature of previous hour, precipitation of previous hour, visibility of previous hour, wind direction of previous hour, the longitudinal component of wind speed and direction of previous hour, the latitudinal component of wind speed and direction of previous hour, pressure of previous hour, wind speed of previous night, temperature of previous night, number of precipitation hours during the previous night, visibility of previous night, wind direction of previous night, the longitudinal component of wind speed and direction of previous night, the latitudinal component of wind speed and direction of previous night, pressure of previous night, date, change in wind speed since previous hour, change in temperature since previous hour, change in precipitation since previous hour, difference in visibility since previous hour, change in pressure since previous hour, change in wind speed since previous 24 hours, change in temperature since previous 24 hours, change in precipitation since previous 24 hours, change in visibility since previous 24 hours, and change in pressure since previous 24 hours. The HMM data spreadsheet is the data used for the Hidden Markov Models portion of the paper. This dataset includes date and rounded-down hour, site ID for weather station area, the standard deviation of signal strength across all detections within one hour, rounded-down hour, number of hours since sunset, number of hours, wind speed, temperature, date, date and time of sunset, date and time of sunrise, sunset hour rounded down, sunrise hour rounded down, binary night or day based on time relative to sunset and sunrise times, sine(hours since sunset * 2 * pi / 24), cosine(hours since sunset * 2 * pi / 24), predicted state (roosting or foraging) based on HMM fit, probability that bat is roosting,probability that bat is foraging, unique identification sequence of individual bat tags,manipulated time-stamp so that all date times share the same year for data visualization, hour and minute of sunset in numeric form for data visualization, and hour and minute of sunrise in numeric form for data visualization. The detection summary data CSV combines capture data with summarized locations and times of detection of radio-tagged eastern red bats (Lasiurus borealis), silver-haired bats (Lasionycteris noctivagans), and Seminole bats (Lasiurus seminolus) captured in the Mid-Atlantic coastal region between August and October of 2019 and 2021 and provides unique dates that each bat was detected at a single tower and/or unique towers that each bat was detected at in a single night. This data set was used for plotting and visualizing individual paths of bats for the qualitative section of the paper (i.e. showing direction, pathway, movement distance, moving at all, etc.). Data contained include detection date, tag ID, tower receiver ID, tower receiver latitude, tower receiver longitude, species name, sex, age (adult or juvenile), weight (g), and forearm length (mm).