# ts.meta.depths: Calculate physical indices for a timeseries. In rLakeAnalyzer: Lake Physics Tools

## Description

Functions for simplifying the calculation of physical indices for a timeseries of observation data. Can usually be called directly on data loaded directly using `load.ts` and `load.bathy`.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ``` ts.meta.depths(wtr, slope = 0.1, na.rm=FALSE, ...) ts.thermo.depth(wtr, Smin = 0.1, na.rm=FALSE, ...) ts.schmidt.stability(wtr, bathy, na.rm=FALSE) ts.lake.number(wtr, wnd, wnd.height, bathy, seasonal=TRUE) ts.uStar(wtr, wnd, wnd.height, bathy, seasonal=TRUE) ts.internal.energy(wtr, bathy, na.rm=FALSE) ```

## Arguments

 `wtr` A data frame of water temperatures (in Celsius). Loaded using `load.ts`. Must have columns `datetime`, `wtr_##.#` where ##.# is depth in meters. `slope` The minimum density gradient (kg/m^3/m) that can be called the thermocline `Smin` The minimum density gradient cutoff (kg/m^3/m) defining the metalimion `bathy` A data frame containing hypsometric data. Loaded using `load.bathy` `wnd` A data frame of wind speeds (in m/s). Loaded using `load.ts` `wnd.height` Height of the anemometer above the lake surface in meters `seasonal` Boolean indicating if seasonal thermocline should be used in calculation. `na.rm` Boolean indicated if step-by-step removal of NA's should be tried. If false, a timestep with any NA values will return an NA value. If true, best effort will be made to calculate indices despite NA values. `...` Additional parameters passed to underlying base function (e.g., index=TRUE for thermo.depth)

## Details

These are wrapper functions that accept a timeseries of data and call the core physical metric functions (like `schmidt.stability`) on each timestep.

## Value

Returns a data frame with the timeseries of calculated derivatives. All include a ‘datetime’ column, but derivative columns differ between functions.

## Author(s)

Luke Winslow

For loading input data `load.ts`, `load.bathy`.
For the underlying functions operating at each timestep `meta.depths`, `thermo.depth`, `schmidt.stability`, `lake.number`, `internal.energy`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ``` #Get the path for the package example file included exampleFilePath <- system.file('extdata', 'Sparkling.daily.wtr', package="rLakeAnalyzer") #Load sparkling.temp = load.ts(exampleFilePath) #calculate and plot the metalimnion depths m.d = ts.meta.depths(sparkling.temp) plot(m.d\$datetime, m.d\$top, type='l', ylab='Meta Depths (m)', xlab='Date', col='blue') lines(m.d\$datetime, m.d\$bottom, col='red') #calculate and plot the thermocline depth t.d = ts.thermo.depth(sparkling.temp) plot(t.d\$datetime, t.d\$thermo.depth, type='l', ylab='Thermocline Depth (m)', xlab='Date') ```