In SebaStad/rPALM: Create static and dynamic drivers for the urban climate model PALM4U

rPALM

rPALM provides R6 classes to create and edit static drivers for the urban climate model PALM-4U.

Installation

Right now, rPALM is only available via GitHub:

# install.packages("devtools")
devtools::install_github("SebaStad/rPALM")

Example

A simple example to create a static driver from scratch. Lots of information about what and why is yet missing!

library(rPALM)
# First:
# Define a headclass
manual_headclass <- palm_global$new(title = "GIT Example",
                                    author = "sest",
                                    institute = "IBP",
                                    location = "Hoki",
                                    x0 = 0,   # only important for visualization on a map later on
                                    y0 = 0,   # only important for visualization on a map later on
                                    z0 = 0,
                                    t0 = "2018-06-21 12:00:00 +00", # Character with Date in this format, 
                                    # might be important to have correct in later releases of PALM!
                                    lat = 52.502302,   # important for solar radiation
                                    lon = 13.364862,   # important for solar radiation
                                    dx = 5)


manual_class <- palm_ncdf_manual$new(nx = 20, ny = 20, dx = 5,
                                     headclass = manual_headclass)

# Manually set vegetation to short grass
manual_class$data$vegetation_type$vals <- array(3,dim = c(20,20))
# Set one Tree
manual_class$data$vegetation_type$vals[9:11,2:3] <- 6

# Pavement
manual_class$data$pavement_type$vals[,9:11] <- 2

# water 
manual_class$data$water_type$vals[,13:14] <- 2

# buildings
manual_class$data$buildings_2d$vals[5:15, 6:8] <- 20
manual_class$data$building_id$vals[5:15, 6:8]  <- 1
manual_class$data$building_type$vals[5:15, 6:8] <- 3


#Sort Data
manual_class$SortOverlayingdata("BPWV")

# plot
manual_class$plot_area(1,1,20,20)

While basically all data is now available, some cleanup functions have to be called to create the static driver:

# First, create the 3D Buidlings data. It does not do anything different from buildings_2d BUT:
#       1. enables 3D visualization in ParaView (so it is mandatory)
#       2. enables the creation of bridges and gates (has to be done manually, time expensive)
manual_class$createbuilding3D(TRUE, FALSE)

# Second, create soil and surface fraction
# Both are mandatory for the simulation
manual_class$addsoilandsurfacefraction(type_soil = 2)


# Third generate LAD
manual_class$generate_lai_array(dz = 5, fixed_tree_height = 15)
# That function has a lot of variables, but these are enough. dz is mandatory

# Fourth, set water temperature to 288K
# Create "water_pars" data 
manual_class$add_lod2_variable("water")
manual_class$data$water_pars$vals[,,1][manual_class$data$water_type$vals>=0] <- 288

# Further functions, that can be useful, but are not needed in this example:

# manual_class$downscale_resolution(factor = 2)
# downscales the resolution by a factor of 2, i.e. from 5 to 10 m

# manual_class$quickplot("vegetation_type")
# allows a quick look at 2D data in the class

# manual_class$savedplots[[1]]
# All plot calls with $plot_area are saved in the list $savedplots

# Count of plots can be called via 
# manual_class$plotcntr


# Finally: set an eportname of the file
manual_class$exportname <- "quicktest.nc"

manual_class

# manual_class$exportncdf()
# Exports the static driver in the current work directory

Data

Data and Dimensions are hold in seperate lists

names(manual_class$data)
names(manual_class$dims)
# Every data has its own sublist
names(manual_class$data$buildings_2d)

The data itself is saved in vals, other variables are important for correct settings in the static driver. The connection between dimensions is done via

manual_class$vardimensions

Here, for every dataset the corresponding dimensions have to be saved!

Cut Out

New function: cutout_static ; enables to cut out a certain domain of the existing domain. DELETES the remaining domain!

One solution is to make a copy via clone(deep = TRUE)

cutout_static <- manual_class$clone(deep = TRUE)
cutout_static$cutout_static(startp = c(3,3), endp = c(18,18), sure = T)

cutout_static$plot_area(1,1,15,15)

PIDS

PIDS should be callable via

# rPALM:::PIDS
rPALM:::PIDS$soil$predefined_type

Also contains building pars now!

SebaStad/rPALM documentation built on June 4, 2024, noon