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RWikience: introduction tutorial

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All data in Climate Wikience are directly accessible from R using RWikience package

RWikience package allows to retrieve raster, time series data from Climate Wikience to R and also contains related utility fuctions. Steps to get data into R:

  1. Download and install R from
  2. Download and install an IDE like RStudio
  3. Install rJava package (you will need this to run RWikience)
  4. You can install rJava by typing the following code in R console:
  5. Download RWikience package and install it into R
  6. RWikience_path <- "path to where you downloaded RWikience package tar.gz";
    install.packages(RWikience_path, repos = NULL, type = "source")
    # Example (use "/" or "\\" in Windows):
    RWikience_path <- "C:/Users/User/WikienceFiles/RWikience_1.1-0.tar.gz"
    install.packages(RWikience_path, repos = NULL, type = "source")
  7. Launch Climate Wikience (RWikience will work only when Climate Wikience is currently running)

The following two commands are required to start working with RWikience

# Load RWikience package
# Connect to running instance of Climate Wikience on your PC

To retrieve global maps (raster data), use getFloatMatrix function:

# Retrieve global matrix of NO2 concentration for 1-st of October 2004
m <- getFloatMatrix(w, "OMI.Nitrogen dioxide.ColumnAmountNO2TropCloudScreened", "01 10 2004")

To enable many other ways of processing data, convert the matrix to “raster” type of “raster” package:

# Load "raster" package
# Convert to R type "raster"
r <- convertToRaster(m)

Simply type “r” to view the properties of newly created raster:

> r
class       : RasterLayer 
dimensions  : 720, 1440, 1036800  (nrow, ncol, ncell)
resolution  : 0.25, 0.25  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +datum=WGS84 
data source : in memory
names       : layer 
values      : -6.343879e+15, 4.233803e+16  (min, max)

Create 2-D map of the global NO2 distribution:

# Visualize raster

You can retrieve other maps in the same way:

m <- getFloatMatrix(w, "MERRA.Wind.Eastward (u).10 m", "01 08 2010")
r <- convertToRaster(m)
m <- getFloatMatrix(w, "Modis L3 Atmosphere.AEROSOL.LAND AND OCEAN.Optical Depth.Maximum", "04 08 2005")
r <- convertToRaster(m)

You can take a full dataset name to forward in to “getFloatMatrix” by simply activating it in Climate Wikience and copying its names from Time Slider drop-down box or Properties drop-down box.

R code used in this tutorial [wpdm_file id=7]