Code adapted from: http://www.r-bloggers.com/consultants-chart-in-ggplot2/ with changes to work with latest version of ggplot2 & to include error bars.

Prepare data:

require(ggplot2)
# function to compute standard error of mean
se <- function(x) sqrt(var(x)/length(x)) 

# set seed for reproducible results
set.seed(9876) 

# create toy data
DF <- data.frame(variable = as.factor(1:10),
                 value = sample(10, replace = TRUE))

DF

##    variable value
## 1         1     9
## 2         2     4
## 3         3     2
## 4         4     6
## 5         5     5
## 6         6     3
## 7         7     5
## 8         8     7
## 9         9     6
## 10       10     2

Create bar plot:

plot <- ggplot(DF, aes(variable, value, fill = variable)) +
  geom_bar(width = 1, stat = "identity", color = "white") +
  geom_errorbar(aes(ymin = value - se(DF$value), 
                    ymax = value + se(DF$value), 
                    color = variable), 
                    width = .2) + 
  scale_y_continuous(breaks = 0:nlevels(DF$variable)) +
  theme_gray() +
  theme(axis.ticks = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        axis.line = element_blank())
plot 

Create windrose/polar plot from this bar plot by converting to a polar coordinate system:

plot + coord_polar() 

To add gridlines, see: http://www.r-bloggers.com/consultants-chart-in-ggplot2/