Welcome to the Ranadu wiki!

The functions in this package provide R access to the netCDF files produced by the NCAR/EOL Research Aviation Facility. Those files contain measurements made in field campaigns that use the NSF research aircraft operated by NCAR, consisting of a C-130 and a Gulfstream V. A list of recent projects is available at http://www.eol.ucar.edu/all-field-projects-and-deployments/, and data requests can be made via links on that page.

The standard data archives consist of netCDF files that contain a set of measurements each second during a flight. The Ranadu functions produce R data.frames containing subsets of those measurements and then facilitate plotting and analyses using those data.frames. This link provides a list of the functions. There is a more extensive discussion of this package in the manual; see "inst/RanaduManual.pdf".

There are several groups of functions that serve different purposes:

1. Functions for data access: getNetCDF(), standardVariables(), setVariableList(), TimeRoutines()

2. Functions that implement calculation algorithms for derived measurements: TrueAirspeed(), WindProcessor(), PitchCorrection(), AirTemperature(), DPfromE(), PCorFunction() and others

3. Convenience functions for plots: plotTrack(), plotWAC(), skewT(), contourPlot(), plotSD()

4. Utilities for handling and examining data: makeNetCDF(), TellAbout(), ValueOf(), getAttributes()

5. Miscellaneous functions for analysis: DemingFit(), LagrangeInterpolation(), binStats(), VSpec()

6. Functions to improve measurements: CorrectPitch(), CorrectRoll(), CorrectHeading()

When data.frames are created, global attributes in the netCDF file become attributes of the generated data.frame and variable attributes in the netCDF file are associated with column variables in the data.frame. Other information in the netCDF file is also stored with the data.frame, so the data.frame becomes a full representation of the netCDF file and complete netCDF files can be re-generated from the data.frames. However, usually data.frames are generated with only subsets of the data needed for particular analysis routines. They therefore can be small and suitable for archiving with analysis projects to document the data as used for the project.

Because these functions are assembled into an R package, they each have associated usage information. This wiki is intended to provide additional information regarding the basis for the algorithms used, the limitations of the functions, and more general documentation. Some of the functions (will) have their own pages for this information.

A general reference for the processing algorithms is this document. Many of the algorithms described there have corresponding functions in this package that implement the algorithms.

There are two sample datasets included with this package. One is the data.frame "RAFdata", which is an example of the data.frames that these functions expect and generate. The other is a small netCDF file, similar to the format of the data-archive files but much smaller, called "RAFdata.nc". It has variables that correspond to those in the "RAFdata" data.frame.

Some of these functions have back-up documentation in papers, reports, and notes either published or under review.This information will be added here eventually, but for now it is worth noting that the "AMTD-AAC" repository contains documentation relevant to the CorrectPitch(), CorrectRoll(), and CorrectHeading() functions that hold the potential for making significant improvements to the measurements of wind.