R-CMD-check CRAN_Status_Badge codecov DOI

The skylight package returns sky illuminance parameters for both the sun and the moon, for a given date/time and location. In addition, ancillary parameters such as sun and moon azimuth and altitude are provided. The code is an almost verbatim transcription of the work by Janiczek and DeYoung (1987), published in the US Naval observatory circular. An online copy of this manuscripts can be found on the internet archive (https://archive.org/details/DTIC_ADA182110).

Very few adjustments to the original code where made to ensure equivalency in results. As such, most of the naming of the subroutines and variables was retained. However, some changes were made to the main routine and subroutines to ensure vectorization of the code to speed up batch processing of data.

With time more detailed information will be added to all functions, including references to subroutine functions and more transparent variable names, while limiting variable recycling (a common practice in the original code base). The code delivers equivalent results with the programme certification values published in Table A of Janiczek and DeYoung (1987), as such all original limitations remain (see below).

How to cite this package in your article

Hufkens, K. et al. (2023) ‘Evaluating the effects of moonlight on the vertical flight profiles of three western palaearctic swifts’. Royal Society Proceedings B. doi: 10.1098/rspb.2023.0957, in addition reference the original work by Janiczek and DeYoung (1987, see below)


The sky illuminance model by Janiczek and DeYoung (1987) in skylight has some limitations:

  • Design specifications aimed for 0.5 degrees in angle, or two minutes of times. Last digits should be considered uncertain by one unit.
  • At latitudes less than 60 degrees, the model should agree with more refined calculations to within one or two minutes of time. For latitudes above this value the model can produce errors of up to four minutes.
  • In some circumstances calculated illuminance values might differ from real light levels of a factor 10 or more.
  • Strong coherence and proper time keeping is required, there is a strong requirement to provide dates in GMT, corrections based upon latitude (not civil time zone) should be executed before processing. No warnings are provided.

Yet, overall the model should provide a fast approximation where more computationally expensive models would only provide marginal benefits for most applications. For a full description of the model I refer to Janiczek and DeYoung (1987).


stable release

To install the current stable release use a CRAN repository:

development release

To install the development releases of the package run the following commands:


Vignettes are not rendered by default, if you want to include additional documentation please use:

remotes::install_github("bluegreen-labs/skylight", build_vignettes = TRUE)


Single date/time and location

skylight values can be calculated for a single point and date using the below call. This will generate a data frame with model values.

# load the library

# calculate sky illuminance values for
# a single date/time and location
df <- skylight(
      longitude = -135.8,
      latitude = -23.4,
      date = as.POSIXct("1986-12-18 21:00:00", tz = "GMT"),
      sky_condition = 1

Multiple dates/times and/or locations

The skylight function is vectorized, so you can provide vectors of input parameters instead of using a loop and the above function call.

# Generate a dataset with 15 minute values
# for approximately two months
input <- data.frame(
  longitude = 0,
  latitude = 50,
  date =  as.POSIXct("2020-06-18 00:00:00", tz = "GMT") + seq(0, 60*24*3600, 900),
  sky_conditions = 1

# calculate sky illuminance values for
# a single date/time and location
df <- skylight(

# previous results are of the same dimension (rows)
# as the input data and can be bound together
# for easy plotting
input <- cbind(input, df)

Plotting this data results in

Piped data workflow

skylight supports piped data frames with appropriatedly named columns as input to the function. This allows for fast processing of large data frames, with the added advantage that input parameters are returned with the calculated data.

Note that you need a data frame with the three most basic parameters: - longitude - latitude - date named as such (all lower case). The function will complain if it doesn’t find the required column names. Also note that due to the priority of the piped construction over the other parameters all parameters should be named when calling the function in a conventional way.

# recreating the data frame with parameters
# as before
input <- data.frame(
  longitude = 0,
  latitude = 50,
  date =  as.POSIXct("2020-06-18 00:00:00", tz = "GMT") + seq(0, 1*24*3600, 1800),
  sky_condition = 1

# but now using the piped approach to calculate
# all values

df <- input |> skylight()

Speed and other considerations

The current code, using the vectorized piped approach, is sufficiently fast to support larger data sets. For example a more advanced cloud cover correction is described in the vignettes and taking this analysis as inspiration animations of illuminance can be made (as shown below).


The skylight package is distributed under a AGPLv3 license, while the skylight model code resides in the public domain made available by Janiczek and DeYoung (1987). The logo is in part based upon Emoji One v2.0 iconography.