R Code for Climate Mathematics:
Theory and Applications
A Cambridge University Press book By
SSP Shen and RCJ Somerville
Version 1.0 released in July 2019 and coded by Dr. Samuel Shen, Distinguished Professor
San Diego State University, California, USA
Email: sshen@sdsu.edu
Version 2.0 compiled and updated by Momtaza Sayd
San Diego State University May 2021
Version 3.0 compiled and updated by Joaquin Stawsky
San Diego State University June 2022
Chapter 5: Energy Balance Models Energy Balance Models for Climate
Plot Fig. 5.2
#NASA Diviner Data Source:
#http://pds-geosciences.wustl.edu/lro/lro-l-dlre-4-rdr-v1/lrodlr_1001/data/gcp/
setwd("~/sshen/climmath")
d19 <- read.table("data/tbol_snapshot.pbin4d-19.out-180-0.txt",header = FALSE)
dim(d19)## [1] 259200 3#[1] 259200 3 #259200 grid points at 0.5 lat-lon resolution
#259200=720*360, starting from (-179.75, -89.75) going north
#then back to south pole then going north until the end (179.75, 89.75)
m19 <- matrix(d19[,3],nrow = 360)
dim(m19)## [1] 360 720library(maps)## Warning: package 'maps' was built under R version 4.1.3Lat1 <- seq(-89.75,by = 0.5,len = 360)
Lon1 <- seq(-189.75,by = 0.5, len = 720)
mapmat <- t(m19)
# mapmat <- pmin(mapmat,10)
# mapmat <- mapmat[,seq(length(mapmat[1,]),1)]#, no flipping
#plot.new()
#png(filename = paste("Moon Surface Temperature, Snapshot=", 19,".png"),
# width = 800, height = 400)
int <- seq(0,400,length.out = 40)
rgb.palette <- colorRampPalette(c('skyblue', 'green', 'blue', 'yellow', 'orange',
'pink','red', 'maroon', 'purple', 'black'),interpolate = 'spline')
filled.contour(Lon1, Lat1, mapmat, color.palette = rgb.palette, levels = int,
plot.title = title("Moon Surface Temperature Observed by NASA Diviner,\n Snapshot 19",
xlab = "Longitude", ylab = "Latitude"
,cex.lab = 1.2,cex.axis = 1.2),
plot.axes = {axis(1); axis(2);grid()},
key.title = title(main = "K"))
#dev.off()
Plot the equator temperature for a snapshot
#plot.new()
#png(filename = paste("Moon's Equatorial Temperature at Snapshot", 19,".png"),
# width = 600, height = 400)
plot(Lon1,m19[180,],type = "l", col = "red",lwd = 2,
xlab = "Longitude", ylab = "Temperature [K]",
main = "Moon's Equatorial Temperature at Snapshot 19"
,cex.lab = 1.2,cex.axis = 1.2)
text(-100,250,"Nighttime",cex = 2)
text(80,250,"Daytime",cex = 2, col = "orange")
#dev.off()
Plot the noon time meridional temperature for a snapshot
#plot.new()
par(mar = c(3.5,4,2,0.5))
#png(filename = paste("Moon's Noon Time Meridional Temperature at Snapshot", 19,".png"),
# width = 600, height = 400)
plot(Lat1,m19[,540],type = "l", col = "red",lwd = 2,
xlab = "Latitude", ylab = "Temperature [K]",
main = "Moon's Noon Time Meridional Temperature at Snapshot 19",
cex.lab = 1.2,cex.axis = 1.2)
#dev.off()
Compute the bright side average temperature of the moon
bt <- d19[129601:259200,]
aw <- cos(bt[,2]*pi/180)
wbt <- bt[,3]*aw
bta <- sum(wbt)/sum(aw)
bta## [1] 302.7653
Compute the dark side average temperature
dt <- d19[0:12960,]
aw <- cos(dt[,2]*pi/180)
wdt <- dt[,3]*aw
dta <- sum(wdt)/sum(aw)
dta## [1] 124.7387
Equator noon temperature of the moon from an EBM
lat <- 0*pi/180
sigma <- 5.670367*10^(-8)
alpha <- 0.12
S <- 1368
ep <- 0.98
k <- 7.4*10^(-4)
h <- 0.4
T0 <- 260
fEBM <- function(T){(1-alpha)*S*cos(lat*pi/180) -(ep*sigma*T^4 + k*(T-T0)/h)}
#Numerically solve this EBM: fEBM = 0
uniroot(fEBM,c(100,420))## $root
## [1] 383.6297
##
## $f.root
## [1] -0.0002452205
##
## $iter
## [1] 6
##
## $init.it
## [1] NA
##
## $estim.prec
## [1] 6.103516e-05
Plot Fig. 5.5
#Define a piecewise albedo function
a1 <- 0.7
a2 <- 0.3
T1 <- 250
T2 <- 280
ab <- function(T) {ifelse(T < T1, a1, ifelse(T < T2,((a1-a2)/(T1-T2))*(T-T2)+ a2, a2))}
#Define the range of temperature
T <- seq(200,350,len = 200)
#Plot the albedo as a nonlinear function of T
#setwd("/Users/sshen/climmath")
#png(file = "fig05-05.png", width = 400, height = 300)
par(mar = c(4,4,4,3))
plot(T, ab(T), type = "l", lwd = 2.0,
ylim = c(0,1), xlab = "Surface Temperature [K]",
ylab = "Albedo", main = "Nonlinear Albedo Feedback"
,cex.lab = 1.2,cex.axis = 1.2)