aemetools is designed to work with AEME. It contains a range of functions to assist in setting up simulations for a lake site.

This package was developed by LimnoTrack as part of the Lake Ecosystem Research New Zealand Modelling Platform (LERNZmp) project.

Currently, this package can be used to:

• Download meteorological data from ERA5-Land for any point in New Zealand from 1980-2023, or download ERA5-Land GRIB files for any area in the world.
• Set up and run hydrological simulations using the suite of models from the airGR package using catchment, reach and lake data.
• Conduct a sensitivity analysis on the parameters for the AEME models.
• Calibrate the AEME models using lake observational data.

You can install the development version of aemetools from GitHub with:

# install.packages("devtools")
devtools::install_github("limnotrack/aemetools")

library(aemetools)

Currently, there is ERA5-Land data (~9km grid spacing) archived for New Zealand (166.5/-46.6/178.6/-34.5) for the time period 1980-2023 with the main meteorological variables (air temperature, dewpoint temperature, wind u-vector at 10m, wind v-vector at 10m, total precipitation, snowfall, surface level pressure, downwelling shortwave radiation, downwelling longwave radiation) required to drive hydrological and hydrodynamic models. This can be easily downloaded using the example below. There is a parallel switch which allows you to use multiple cores on your computer to speed up the download.

lon <- 176.2717
lat <- -38.079
vars <- c("MET_tmpair", "MET_pprain")

met <- get_era5_land_point_nz(lat = lat, lon = lon, years = 2020:2021,
                      vars = vars)
summary(met)
#>       Date              MET_tmpair       MET_pprain      
#>  Min.   :2020-01-01   Min.   : 4.848   Min.   : 0.00000  
#>  1st Qu.:2020-07-01   1st Qu.: 9.699   1st Qu.: 0.08205  
#>  Median :2020-12-31   Median :12.729   Median : 0.83960  
#>  Mean   :2020-12-31   Mean   :12.845   Mean   : 5.10542  
#>  3rd Qu.:2021-07-01   3rd Qu.:15.782   3rd Qu.: 5.73165  
#>  Max.   :2021-12-31   Max.   :22.176   Max.   :53.44960

library(ggplot2)
library(tidyr)

met |> 
  pivot_longer(cols = c(MET_tmpair, MET_pprain)) |> 
  ggplot(aes(x = Date, y = value)) +
  geom_line() +
  facet_wrap(~name, scales = "free_y", ncol = 1) +
  theme_bw()

See the vignette here.

See the vignette here.

See the vignette here.