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Using a Raster Stack to compute averages across land or ocean only

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I am interested in calculating precipitation averages globally. However, I only want to isolate land and/or oceanic areas to compute the mean of those separately. What I would like to do is somehow isolate those grid cells whose centers overlap with either land or ocean and then compute the annual mean. I already first created a raster stack, called "RCP1pctCO2Mean", which contains the mean values of interest. There are 138 layers, with each layer representing one year. This raster stack has the following attributes:

class       : RasterStack 
dimensions  : 64, 128, 8192, 138  (nrow, ncol, ncell, nlayers)
resolution  : 2.8125, 2.789327  (x, y)
extent      : -181.4062, 178.5938, -89.25846, 89.25846  (xmin, xmax, ymin,  
ymax)
coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
names       :    layer.1,    layer.2,    layer.3,    layer.4,    layer.5,       
layer.6,    layer.7,    layer.8,    layer.9,   layer.10,   layer.11,   
layer.12,   layer.13,   layer.14,   layer.15, ... 
min values  : 0.42964514, 0.43375653, 0.51749371, 0.50838983, 0.45366730,    
0.53099146, 0.49757186, 0.45697752, 0.41382199, 0.46082401, 0.45516687, 
0.51857087, 0.41005131, 0.45956529, 0.47497867, ... 
max values  :   96.30350,  104.08584,   88.92751,   97.49373,   89.57201,   
90.58570,   86.67651,   88.33519,   96.94720,  101.58247,   96.07792,   
93.21948,   99.59785,   94.26218,   90.62138, ...  

Previously, I tried isolating a specific region by specifying a range of longitudes and latitudes to obtain the means and medians for that region, just like this:

expansion1<-expand.grid(103:120, 3:15) #This is a range of longitudes and then latitudes
lonlataaa<-extract(RCP1pctCO2Mean, expansion1)
Columnaaa<-colMeans(lonlataaa)

#Packages loaded

library(raster)
library(maps)
library(maptools)
library(rasterVis)

However, with this approach, too much water can mix with land areas, and if I narrow the latitude/longitude range on land, I might miss too much land to compute the mean meaningfully. Therefore, with this RasterStack, would it be possible to create a condition that tells R that if the "center point" or centroid of each grid cell (with each grid cell center representing a specific latitude/longitude coordinate) happens to fall on land, then it would be considered as land (i.e. that would be TRUE - if not, then FALSE, or maybe somehow use 0s or 1s)? Even if a grid cell happens to have water mixed with land, but the center point/centroid of the grid is on land, that would be considered as land. I would like to do this for specific countries, too.

What I was thinking was maybe using wrld_smpl from the maptools package to somehow create a mask that hides oceans, and then somehow have only those grid cells from the "RCP1pctCO2Mean" RasterStack overlap accordingly with the land/water polygons that would be left behind, or for any country that I am interested in.

Is there a way to do this?

Thank you, and I would greatly appreciate any assistance!


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