PEcAn: Importing Met data from Bondville, IL Ameriflux station

Overview

This is a demonstration of the PEcAn utilities for downloading met data, converting it to the PEcAn-CF format (which is based on the Climate Forecasting conventions and similar to MsTMIP). These variables are described in the PEcAn met data documentation.

We’ll download 12 years of met data from the Bondville Ameriflux site, which has a SITE_ID of US-Bo1.

The PEcAn.data.atmosphere source code is in modules/data.atmosphere and the documentation can be found with either package?PEcAn.data.atmosphere or in the data.atmosphere package documentation.

library(knitr)
library(PEcAn.data.atmosphere)

Download Ameriflux data for Bondville

download.Ameriflux(sitename = "US-Bo1", outfolder = "/tmp/", 
                   start_date = "1996-01-01", end_date = "2008-04-10")

Convert to PEcAn-CF format

met2CF.Ameriflux(in.path = "/tmp/", in.prefix = "US-Bo1", outfolder = "/tmp/out/", 
                 start_date = "1996-01-01", end_date = "2008-04-10")

Concatenate years

NB: this is not required within PEcAn; used here for convenience. See documentation for NCO ncrcat function.

system("ncrcat -O -h /tmp/out/US-Bo1.199[6789].nc /tmp/out/US-Bo1.200[12348678].nc /tmp/out/US-Bo11996-2008.nc")

Load

Using the load.cfmet convenience function. Ameriflux is provided at 30 min intervals. If needed at a finer resolution, see ?cfmet.downscale.time (which works with subdaily and daily data). There is no cfmet.upscale.time function, but would be straightforward to implement if needed.

bondville.nc <- nc_open("/tmp/out/US-Bo11996-2008.nc")
bondville.cfmet <- load.cfmet(bondville.nc, lat = 40.0061988830566, lon = -88.290397644043, start.date = "1996-08-25", end.date = "2008-04-10")[!is.na(air_pressure)]
library("ggplot2", logical.return = TRUE)  || stop("Skipping this chunk because ggplot2 not found")

theme_set(theme_tufte())
p1 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = surface_downwelling_shortwave_flux_in_air)) + ylab(paste(bondville.nc$var$surface_downwelling_shortwave_flux_in_air$longname, bondville.nc$var$surface_downwelling_shortwave_flux_in_air$units))

p2 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = surface_downwelling_longwave_flux_in_air)) + 
 ylab(paste(bondville.nc$var$surface_downwelling_longwave_flux_in_air$longname, bondville.nc$var$surface_downwelling_longwave_flux_in_air$units))

p3 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = surface_downwelling_photosynthetic_photon_flux_in_air)) + ylab("PAR umol/m2/s")

p4 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = air_pressure)) + 
   ylab(paste(bondville.nc$var$air_pressure$longname, bondville.nc$var$air_pressure$units))

p5 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = air_temperature )) + 
   ylab(paste(bondville.nc$var$air_temperature$longname, bondville.nc$var$air_temperature$units))

p6 <- ggplot(data = bondville.cfmet, aes(x = date)) + 
  geom_line(aes(y = wind_speed)) + 
  #geom_line(aes(y = northward_wind), color = 'blue', alpha = 0.3) + 
  #geom_line(aes(y = eastward_wind), color = 'red', alpha = 0.3) + 
  #ggtitle("wind speed: scalar (black) north vector (blue) and east vector (red) ") + 
   ylab(paste(bondville.nc$var$wind_speed$longname, bondville.nc$var$wind_speed$units))

p7 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = relative_humidity )) + 
   ylab(paste(bondville.nc$var$relative_humidity$longname, bondville.nc$var$relative_humidity$units))

p8 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = specific_humidity )) + 
   ylab(paste(bondville.nc$var$specific_humidity$longname, bondville.nc$var$specific_humidity$units))

p9 <- ggplot() + geom_line(data = bondville.cfmet, aes(x = date, y = precipitation_flux))  +
   ylab(paste(bondville.nc$var$ precipitation_flux$longname, bondville.nc$var$precipitation_flux$units))


plots <- list(p1, p2, p3, p4, p5, p6, p7, p8, p9)

Plot entire time series

Plot 8-26-1996 to 10-14-1996

Convert to BioCro Model format

To use the data, you can convert these to a model specific format

library(PEcAn.BIOCRO)
# met2model.BioCro uses the following
bondville.biocromet <- cf2biocro(bondville.cfmet, longitude = -88.0, zulu2solarnoon = TRUE)

# write as csv for sharing 
write.csv(bondville.biocromet, "../soy/data/bondville_1996-2008.csv", row.names = FALSE)