CSLS_find_common_dates: Given CSLS data, find common dates of record
In WDNR-Water-Use/CSLSevap: Evapo(transpi)ration Calculations

Description Usage Arguments Details Value

Finds date interval with records for lst, weather, and lake levels. Checks for the latest "start" date in each of these timeseries, then checks for the earliest "end" date in each timeseries, then restricts all input data to be within the overlapping interval. Lastly, interpolates the lake_levels dataset over NA values to ensure a continuous timeseries of lake area and lake depth for evaporation calculations.

1	CSLS_find_common_dates(weather, lake_levels, lst)

`weather`	a data frame with hourly weather data incl. air temperature (atmp), relative humidity (RH), incoming solar radiation (Rs), precipitation (P), and wind speed (wind).
`lake_levels`	a data frame with daily water level measurements as formatted in the lake_levels dataset, subset to lake level records for the lake of interest.
`lst`	a data frame with sub-monthly lake surface temperature measurements as formatted in the lst_HOBO dataset, subset for a single lake.

Note that this function may cause undesired behavior when using CSLS_daily_met with the Unmodified Hammon method or the McJannet method with use_lst = FALSE. Neither uses the lst dataset for calculations, yet other input data is restricted based on the availability of the lst dataset. Unmodified Hamon also does not use lake_levels, but is restricted by the avilability of that dataset as well.

a list with the following items:

`weather`	same as input weather data frame, but filtered to only include data during the overlap time period
`lst`	same as input lst data frame, but filtered to only include data during the overlap time period and summarized at a daily time step
`lake_levels`	same as input lake_levels data frame, but filtered to only include data during the overlap time period and with missing (NA) lake levels interpolated
`wtmp0`	initial lake surface temperatuer (degC) from the day before the weather, lst, and lake_levels timeseries begin