In chepec/photoec: Solar spectra and constants for photoelectrochemistry
title: "The spectrum of a black body"
author: "Taha Ahmed"
date: "r Sys.Date()"
I made an attempt to to load siunitx in Rmd->HTML vignette -- it did not work, broke all LaTeX support
https://stackoverflow.com/a/55531382/1198249
output:
rmarkdown::html_vignette:
includes:
in_header: header.html
also tried header-includes, did not work (but without breaking all LaTeX)
header-includes:
- \usepackage{siunitx}
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{The spectrum of a black body}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
library(dplyr)
library(tidyr)
# to use variables in dplyr::rename
# https://stackoverflow.com/a/67644830/1198249
library(glue)
library(stringr) # str_remove
library(tibble) # add_column
library(knitr)
library(ggplot2)
library(latex2exp)
library(cowplot)
library(ggrepel)
library(gt)
library(xtable)
library(here)
library(common)
options(
digits = 7,
width = 84,
continue = " ",
prompt = "> ",
warn = 0,
stringsAsFactors = FALSE)
opts_chunk$set(
dev = "svg",
fig.align = "center",
fig.width = 7.10,
# 7.10/4.39=1.617 golden ratio
# but we increase height slightly to make allowance for title,
# secondary axis, caption, etc.
fig.height = 4.58,
echo = TRUE,
eval = TRUE,
cache = FALSE,
collapse = TRUE,
results = 'hide',
message = FALSE,
warning = FALSE,
tidy = FALSE)
spectral.min <- 1E-7 # meter
spectral.max <- 4E-6 # meter
spectral.stepsize <- 1E-9 # meter
vis.min <- 380e-9 # m
vis.max <- 780e-9 # m
An ideal absorber absorbs all incident radiation and is called a black body.
By simple conservation of energy, such a black body must then have an emissivity
of unity.
Every object at a temperature above 0 K emits and absorbs electromagnetic radiation
to some degree. The the spectral distribution of a black body depends only
on its temperature.
Stars are not ideal absorbers, but are to a very close approximation black bodies
when considering their surface temperature.
The spectral radiance^[Irradiance is the radiant power emitted by the black body,
and radiance is the radiant power received by another object. That is how these
terms are usually defined in radiometry
and how we use them in this package.]
of a black body (i.e, its emitted power per unit area and per unit wavelength)
at thermal equilibrium is given by Planck's law^[Planck's law describes
the spectral radiance, $I$, of electromagnetic radiation at all wavelengths
emitted in the normal direction from a black body in a cavity in thermodynamic equilibrium.]:
\begin{equation}
I\left(\lambda, T\right) = \frac{2{\pi}hc^2}{\lambda^5}\frac{1}{\exp\left(\displaystyle\frac{hc}{{\lambda}kT}\right) - 1}
\end{equation}
where $h$ is Planck's constant, $c$ is the speed of light in vacuum, and $k$ is
Boltzmann's constant (please see table below for details on these constants).
To be rigorous, we may note that when referring to a black body the spectral radiance
is considered independent of viewing angle (isotropic), independent of time, and
independent of position on the emitting surface (spatially homogeneous).
Notice that in Planck's law the first term (the fifth-power term) has units of
W m⁻² nm⁻¹ (assuming wavelength was given in nm) and that the second term (the exponential term)
is unitless.
The amount of thermal radiation from a material can be determined by multiplying
its spectral radiance and emissivity. For a black body the spectral radiance thus
completely characterises its thermal output.
This makes Planck's law very useful for modelling the solar radiance as well
as the irradiance on Earth.
xtab.solarconstants <-
photoec::solarconstants |>
select(name, label.html, value, unit.html, reference) |>
xtable::xtable()
names(xtab.solarconstants) <- c("Name", "Symbol", "Value", "Unit", "Reference")
# remember, digits() display() align() are length + 1 (include row.names)
digits(xtab.solarconstants) <- c(0, 0, 0, 4, 0, 0)
display(xtab.solarconstants) <- c("s", "s", "s", "e", "s", "s")
align(xtab.solarconstants) <- c("l", "l", "c", "r", "l", "l")
print(
xtab.solarconstants,
include.rownames = FALSE,
# disabling sanitization is important to not mangle HTML markup inside the dataframe
sanitize.text.function = function(x){x},
type = "html")
It is perhaps instructive to start off by modelling not just the Sun but also
a higher- and a lower-temperature star using Planck's law.
surface.temperature <- c(
# https://en.wikipedia.org/wiki/Gamma_Cassiopeiae # 25000, # K
# https://en.wikipedia.org/wiki/Sirius # 9940, # K
# https://en.wikipedia.org/wiki/Vega # 9602, # K
# https://en.wikipedia.org/wiki/Fomalhaut # 8590, # K
# https://en.wikipedia.org/wiki/Deneb
8525,
# Sun
filter(photoec::solarconstants, label=="T.Sun")$value,
# https://en.wikipedia.org/wiki/Beta_Andromedae # 3842, # K
# https://en.wikipedia.org/wiki/Betelgeuse
3600)
bblong <- NULL
for (i in 1:length(surface.temperature)) {
bblong <- bind_rows(
bblong,
photoec::sunlight.Planck(
wavelength = seq(spectral.min, spectral.max, spectral.stepsize),
temperature = surface.temperature[i]) %>%
# convert spectral radiance/irradiance columns from W m⁻² m⁻¹ to W m⁻² nm⁻¹
mutate(Sun.spectralradiance = 1e-9 * Sun.spectralradiance) %>%
mutate(Earth.spectralirradiance = 1e-9 * Earth.spectralirradiance) %>%
add_column(energy = photoec::wavelength2energy(.$wavelength), .after = "wavelength") %>%
add_column(temperature = surface.temperature[i], .after = "energy") %>%
pivot_longer(
cols = !starts_with(c("wavelength", "energy", "temperature")),
names_to = "property",
values_to = "value"))
}
In the above chunk we used Planck's law as implemented by our sunlight.Planck()
function to return spectral radiance as well as other derived quantities
for three different absolute temperatures.
# you want to be careful when extending the wavelength range towards larger values that
# you don't use too large step sizes in the lower ranges, because that will mess up
# the cumulative radiance values (due to trapezoidal integration)
# NOTE that adding the two higher-wavelength ranges makes no discernible difference
# to the calculated totals or visible range fractions
wl.extended <- c(seq(1E-9, 2E-5, 1E-9), seq(3E-05, 1, 1E-4), seq(2, 1E6, 1E2))
radiances <- NULL
for (i in 1:length(surface.temperature)) {
radiances <- bind_rows(
radiances,
photoec::sunlight.Planck(
wavelength = wl.extended,
temperature = surface.temperature[i]) %>%
add_column(temperature = surface.temperature[i], .after = "wavelength") %>%
select(wavelength, temperature, Sun.radiance) %>%
rename(total = Sun.radiance) %>%
# find the total radiance (last value in vector, corresponds to largest wavelength)
group_by(temperature) %>%
slice_tail(n = 1)
)
}
# to avoid stupid errors due to temperatures possibly ordered differently, use join
radiances <-
left_join(
radiances,
bblong %>%
group_by(temperature) %>%
filter(property == "Sun.radiance") %>%
# careful, this equals sign only works reliably if stepsize 1 nm
filter(wavelength == vis.min) %>%
# slice unnecessary if preceding comparison uses ==, but needed if we use > or <
slice_head(n = 1) %>%
select(temperature, value) %>%
# dynamically construct new column name using glue notation
# https://stackoverflow.com/a/67644830/1198249
rename("at{vis.min}" := value),
by = "temperature") %>%
left_join(
bblong %>%
group_by(temperature) %>%
filter(property == "Sun.radiance") %>%
filter(wavelength == vis.max) %>%
slice_head(n = 1) %>%
select(temperature, value) %>%
rename("at{vis.max}" := value),
by = "temperature")
# radiance in the visible range
# note the use of drop=TRUE to force return of vector and not tibble, which is otherwise the default
# https://tibble.tidyverse.org/reference/subsetting.html
radiances$visible <- radiances[, paste0("at", vis.max), drop=T] - radiances[, paste0("at", vis.min), drop=T]
# fraction of radiance in the visible range compared to total radiance
radiances$fraction <- radiances$visible / radiances$total
this.labeller <- setNames(
# note that knitr device=svg throws lot of warnings when we used unicode
# char (no-break space) instead of regular space character here
# https://github.com/yihui/knitr/issues/496
paste0(unique(bblong$temperature), " K"),
unique(bblong$temperature))
p.bb.spradiance <- ggplot(bblong %>% filter(property == "Sun.spectralradiance")) +
facet_wrap(
~temperature, ncol = 1, scales = "free_y",
labeller = as_labeller(this.labeller)) +
# highlight visible spectrum range as area
# would be really cool if we could colour this area as a rainbow...
geom_ribbon(
data = bblong %>%
filter(property == "Sun.spectralradiance") %>%
filter(wavelength >= vis.min & wavelength <= vis.max),
fill = alpha("orange", 0.35),
colour = NA,
ymin = 0,
aes(x = wavelength, ymax = value)) +
geom_path(
aes(
x = wavelength,
y = value)) +
geom_text(
data = radiances,
x = mean(range(vis.min, vis.max)),
# Y=Inf in combination with hjust=1 (note the angle) aligns the right-edge of the text
# with top of plot area. hjust > 1 pushes the text downwards (also affected by textsize).
y = Inf, hjust = 2.65, size = 3.25,
# note that due to angle=90 here vjust affects horizontal positioning
vjust = 0.5, angle = 90,
colour = "#b36200", # dark orange
aes(
label = paste0(formatC(100 * fraction, digits=2), "%"),
group = temperature)) +
geom_label_repel(
data = . %>% group_by(temperature) %>% filter(max(value) == value),
size = 3.0, nudge_x = 1e-6,
point.padding = unit(0.75, "lines"),
arrow = arrow(length = unit(0.05, "npc")),
aes(
label = paste0(numbers2prefix(wavelength), "m"),
x = wavelength,
y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Spectral radiance / kW m⁻² nm⁻¹",
labels = rlang::as_function(~ 1e-3 * .)) +
theme(
legend.position = c(1, 1),
legend.justification = c(1, 1))
p.bb.radiance <- ggplot(bblong %>% filter(property == "Sun.radiance")) +
facet_wrap(
~temperature, ncol = 1, scales = "free_y",
labeller = as_labeller(this.labeller)) +
geom_ribbon(
data = bblong %>%
filter(property == "Sun.radiance") %>%
filter(wavelength >= vis.min & wavelength <= vis.max),
fill = alpha("orange", 0.35),
colour = NA,
ymin = 0,
aes(x = wavelength, ymax = value)) +
geom_path(
aes(
x = wavelength,
y = value)) +
geom_text(
data = radiances,
x = Inf, y = Inf,
vjust = 2.25, hjust = 1.2, size = 3.25,
aes(
label = paste0(formatC(1E-6 * total, format="f", digits = 1), " MW m⁻²"),
group = temperature)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Radiance / MW m⁻²",
labels = rlang::as_function(~ 1e-6 * .)) +
theme(legend.position = "none")
title.cow <- ggdraw() +
draw_label(
"Black body spectra at three different temperatures",
x = 0, hjust = 0, size = 14) +
# manually adjusted title left-side margin to align with left plot panel
theme(plot.margin = margin(0, 0, 0, 40))
subtitle.cow <- ggdraw() +
draw_label(
"Exemplified with Betelgeuse, the Sun, and Deneb. Visible range demarcated in yellow.",
x = 0, hjust = 0, y = 1, size = 10) +
# manually adjusted title left-side margin to align with left plot panel
theme(plot.margin = margin(0, 0, 0, 40))
bb.row <- cowplot::plot_grid(p.bb.spradiance, p.bb.radiance, nrow = 1, rel_widths = c(1, 1))
cowplot::plot_grid(title.cow, subtitle.cow, bb.row, ncol = 1, rel_heights = c(0.1, 0.04, 1))
Visible range (r numbers2prefix(vis.min)m–r numbers2prefix(vis.max)m) shown as
a yellow area under both the spectral radiance and radiance curves, on the former
overlaid with the ratio of radiance in the visible range to the total radiance.
In the right-hand panels the total radiance (calculated by integrating spectral radiances over the
wavelength range r numbers2prefix(min(wl.extended))m–r numbers2prefix(max(wl.extended), digits = 4)m)
is also shown.
The shape of the spectral radiance curve (Planck's law) is only dependent on the
temperature of the black body. The position of the peak of the spectral radiance
shifts depending on the temperature (towards lower wavelengths for higher temperatures).
The wavelength of the spectral radiance's maximimum can be deduced from the
curve itself (i.e., Planck's law), or else from the so-called Wien displacement law,
which is just another way to express the same thing:
\begin{equation}
\lambda_\mathrm{peak} = \frac{b}{T}
\end{equation}
where $T$ is the absolute temperature and $b$ is a proportionality constant
ultimately derived from Planck's law:
\begin{equation}
b = \frac{hc}{xk} \approx 2.89777\ldots\cdot10^{-3} \mathrm{m~K}
\end{equation}
where $h$ is Planck's constant, $c$ is the speed of light, $k$ is Boltzmann's constant,
and $x$ is a purely mathematical constant.^[$x$ is the positive solution to
$x = 5(1 - \exp(-x))$, which is solved by
$x = 5 + W(-5\exp(-5))$, where $W()$ is the Lambert W-function,
and gives $x = 4.965114231744276\ldots$.
But I must admit I don't know what the W-function is. Some function to wrangle this
sort of exponential equation, I suppose.]
Note that as parametrised here, the unit of $b$ is m K (that's metre Kelvin) and nothing else.
dflong <- photoec::sunlight.Planck(wavelength = wl.extended) %>%
# convert spectral radiance/irradiance columns from W m⁻² m⁻¹ to W m⁻² nm⁻¹
mutate(Sun.spectralradiance = 1e-9 * Sun.spectralradiance) %>%
mutate(Earth.spectralirradiance = 1e-9 * Earth.spectralirradiance) %>%
# the use of .$ notation was necessary here (because inside function call, I guess)
add_column(energy = photoec::wavelength2energy(.$wavelength), .after = "wavelength") %>%
# transform dataframe to long format (better suited for tidy and gpplot2)
pivot_longer(
cols = !starts_with(c("wavelength", "energy")),
names_to = "property",
values_to = "value")
dflong %>% glimpse()
# using facetting is not suitable because we have different y-axis for every plot...
p.sun.spradiance <-
ggplot(dflong %>%
filter(property == "Sun.spectralradiance") %>%
filter(wavelength >= spectral.min & wavelength <= spectral.max)) +
geom_line(
aes(
x = wavelength,
y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Sp. radiance / kW m⁻² nm⁻¹",
labels = rlang::as_function(~ 1e-3 * .)) +
theme(legend.position = "none")
p.sun.radiance <-
ggplot(dflong %>%
filter(property == "Sun.radiance") %>%
filter(wavelength >= spectral.min & wavelength <= spectral.max)) +
geom_line(
aes(
x = wavelength,
y = value)) +
geom_text(
# cannot use . here, must be explicit, otherwise we get the data truncated
# at vis.max whereas we want the radiance for the extended spectral range
data = dflong %>%
filter(property == "Sun.radiance") %>%
slice_tail(n = 1),
x = Inf, y = Inf,
vjust = 2.50, hjust = 1.2, size = 3.25,
aes(label = paste0(formatC(1E-6 * value, format = "f", digits = 1), " MW m⁻²"))) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Radiance / MW m⁻²",
labels = rlang::as_function(~ 1e-6 * .)) +
theme(legend.position = "none")
p.sun.luminosity <-
ggplot(dflong %>%
filter(property == "Sun.luminosity") %>%
filter(wavelength >= spectral.min & wavelength <= spectral.max)) +
geom_line(aes(x = wavelength, y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(name = "Luminosity/W") +
theme(legend.position = "none")
##
p.earth.spirr <-
ggplot(dflong %>%
filter(property == "Earth.spectralirradiance") %>%
filter(wavelength >= spectral.min & wavelength <= spectral.max)) +
geom_line(
aes(
x = wavelength,
y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(name = "Sp. irradiance / W m⁻² nm⁻¹") +
theme(legend.position = "none")
p.earth.irr <-
ggplot(dflong %>%
filter(property == "Earth.irradiance") %>%
filter(wavelength >= spectral.min & wavelength <= spectral.max)) +
geom_line(
aes(
x = wavelength,
y = value)) +
geom_text(
# cannot use . here, must be explicit, otherwise we get the data truncated
# at vis.max whereas we want the irradiance for the extended spectral range
data = dflong %>%
filter(property == "Earth.irradiance") %>%
slice_tail(n = 1),
x = Inf, y = Inf,
vjust = 2.50, hjust = 1.2, size = 3.25,
aes(label = paste0(formatC(value, format = "f", digits = 1), " W m⁻²"))) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Irradiance / kW m⁻²",
labels = rlang::as_function(~ 1e-3 * .)) +
theme(legend.position = "none")
p.earth.luminosity <-
ggplot(dflong %>%
filter(property == "Earth.luminosity") %>%
filter(wavelength >= spectral.min & wavelength <= spectral.max)) +
geom_line(aes(x = wavelength, y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(name = "Luminosity/W") +
theme(legend.position = "none")
# https://datavizpyr.com/join-multiple-plots-with-cowplot/
title.cow <- ggdraw() +
draw_label(
paste0(
"Spectrum of the Sun modelled as a black body (",
paste0(1e9 * spectral.min, " nm"),
# en dash
"–",
paste0(1e6 * spectral.max, " µm"),
")"),
x = 0, hjust = 0, size = 14) +
# manually adjusted title left-side margin to align with left plot panel
theme(plot.margin = margin(0, 0, 0, 45))
title.sun <- ggdraw() + draw_label("Solar radiance", angle=-90, x=0.5, y=0, hjust=1.65, vjust=0.5, size=12)
# hjust adjust up/down position of right-side labels and was adjusted manually
title.earth <- ggdraw() + draw_label("Irradiance on Earth", angle=-90, x=0.5, y=0, hjust=1.37, vjust=0.5, size=12)
row.sun <- cowplot::plot_grid(p.sun.spradiance, p.sun.radiance, title.sun, nrow = 1, rel_widths = c(1, 1, 0.1), labels = c("a", "b"), label_x = 0.16, label_y = 0.97)
row.earth <- cowplot::plot_grid(p.earth.spirr, p.earth.irr, title.earth, nrow = 1, rel_widths = c(1, 1, 0.1), labels = c("c", "d"), label_x = 0.16, label_y = 0.97)
cowplot::plot_grid(title.cow, row.sun, row.earth, ncol = 1, rel_heights = c(0.1, 1, 1))
Figure above shows the spectral radiance and radiance of the Sun
and the spectral irradiance and radiance at Earth's surface
(note that at this level of abstraction the thickness of
the atmosphere is all but irrelevant).
Note that just as earlier the displayed total radiance values (in the right-hand panels)
are based on the extended wavelength range
r numbers2prefix(min(wl.extended))m–r numbers2prefix(max(wl.extended), digits = 4)m.^[By
taking a wider wavelength range into account we get a better approximation of the total radiance.
For example calculating the total irradiance on Earth when limited to the plotted wavelength range
yields a value of
r dflong %>% filter(property == "Earth.irradiance") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max) %>% slice_tail(n=1) %>% pull(value) %>% formatC(digits=1, format="f") W m⁻².]
Let's take a closer look at the two terms in Planck's law, i.e., the power term
and the exponential term.
Both terms vary with many orders of magnitude over the solar spectral range which
makes them awkward to plot, so instead we will look at their values at the spectral
range extremes.
The power-term goes from
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(wavelength) %>% numbers2prefix()m
to
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(wavelength) %>% numbers2prefix()m,
i.e., a difference of eight orders of magnitude.
Notice how it goes from extremely large values at low wavelength to very large values
at long wavelengths. But it does continue dropping (as power laws do, asymptotically towards
zero) so that by a wavelength of 1 m it is 1e-16 W m⁻² nm⁻¹ and four orders of magnitude later
(i.e, at a wavelength of 10 km) it is 1e-36 W m⁻² nm⁻¹ (20 orders of magnitude smaller).
dflong %>% filter(property == "Sun.spectralradiance.powerterm") %>% head()
dflong %>% filter(property == "Sun.spectralradiance.powerterm") %>% tail()
The exponential term goes from
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(wavelength) %>% numbers2prefix()m
to
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(wavelength) %>% numbers2prefix()m,
i.e., a difference of 11 orders of magnitude.
dflong %>% filter(property == "Sun.spectralradiance.expterm") %>% head()
dflong %>% filter(property == "Sun.spectralradiance.expterm") %>% tail()
From the above results we can see that the powerterm drops much faster than the exponential
rises, giving us the spectral radiance curve that slowly drops to almost zero at high wavelengths.
And despite the powerterm growing towards lower wavelengths, it is still outmatched
by the much stronger drop in the exponential (which in fact goes to zero), giving
the spectral radiance curve that drops quickly towards zero at the lowest wavelengths.
In fact, the spectral radiance goes above 1e-30 W m⁻² nm⁻¹ only by a wavelength of 25 nm,
and above 1 µW m⁻² nm⁻¹ only at wavelengths above 62 nm.
As we saw the slope is less extreme towards higher wavelengths.
By 530 µm the spectral radiance has dropped to the microwatt level again, but does not
drop to around 1e-30 W m⁻² nm⁻¹ until a wavelength of around 400 m (yes, that's meters).
So based purely on Planck's law, in order to estimate the Sun's black body total
radiant power to a high degree of accuracy, we should use a wavelength range from
at least 25 nm to 400 m.
Note that for estimating total radiant power not only the spectral radiance,
but also the spectral flux matters. That is, despite high-energy gamma rays being
extremely energetic (wavelengths down to $10^{-17}$ nm or
r common::numbers2prefix(photoec::wavelength2energy(1e-17))eV which is beyond
even our most powerful particle accelerators, I believe) the amount of such
photons is effectively zero, as we saw above.
Note that the total radiant power values given in the plots above integrated
radiance over an even wider wavelength range,
r numbers2prefix(min(wl.extended))m–r numbers2prefix(max(wl.extended), digits = 4)m.
# 3.74e19 W m⁻² nm⁻¹ at 1 nm, drops to 3.654e11 at 4000 nm (8 orders of magnitude)
p <- ggplot(data = bblong %>%
filter(property == "Sun.spectralradiance.powerterm") %>%
filter(temperature == filter(solarconstants, label == "T.Sun")$value)) +
coord_cartesian(y = c(0, 1e13)) +
geom_line(
aes(
x = wavelength,
y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Spectral radiance / W m⁻² nm⁻¹") +
# labels = rlang::as_function(~ 1e-6 * .)) +
theme(legend.position = "none")
# 1.49e-11 W m⁻² nm⁻¹ at 1 nm, rises to 1.16 at 4000 nm (11 orders of magnitude)
ggplot(data = bblong %>%
filter(property == "Sun.spectralradiance.expterm") %>%
filter(temperature == filter(solarconstants, label == "T.Sun")$value)) +
# coord_cartesian(y = c(0, 1e13)) +
geom_line(
aes(
x = wavelength,
y = value)) +
scale_x_continuous(
name = "Wavelength / nm",
labels = rlang::as_function(~ 1e9 * .)) +
scale_y_continuous(
name = "Spectral radiance / W m⁻² nm⁻¹",
sec.axis = dup_axis()) +
# labels = rlang::as_function(~ 1e-6 * .)) +
theme(legend.position = "none")
We should perhaps mention how we calculate the irradiance on Earth from the solar
radiance values. The distance between the Earth and the Sun varies over the year,
but for our purposes the astronomical unit has sufficient precision.
We assume the solar radiance (power per unit area) is spread evenly across the entire
surface of the Sun (isotropic radiation), and since the Earth radius is tiny compared
to the Sun and the distance between them is huge only a miniscule fraction of the
solar radiance can impinge on the planet.
We can calculate this fraction by a little geometry: consider two spheres centered on
the Sun, one with a radius equal to the Sun, and the other with a radius of Earth's
orbit (i.e., 1 AU). The fraction we seek (or in other words an attenuation factor) is
the squared quotient of the inner sphere's radius to the outer sphere's radius,
$R_\mathrm{Sun}/R_\mathrm{Earth}$ =
r (filter(photoec::solarconstants, label=="R.Sun")$value / filter(photoec::solarconstants, label=="R.AU")$value)^2 %>% formatC(format="e", digits=2).
You may have already noticed that this geometric argument is just another way to express
the inverse square law:
\begin{equation}
I_\mathrm{Earth} = I_\mathrm{Sun} \frac{4\pi R_\mathrm{Sun}^2}{4\pi R_\mathrm{Earth}^2} =
I_\mathrm{Sun} \left(\frac{R_\mathrm{Sun}}{R_\mathrm{Earth}}\right)^2
\end{equation}
Sources
- Nilsson, A.M., 2012. Daylighting systems: development of techniques for optical
characterization and performance evaluation (PhD thesis). Uppsala university, Uppsala.
- Bayrak Pehlivan, I., 2013. Functionalization of polymer electrolytes for
electrochromic windows (PhD thesis). Uppsala university, Uppsala.
- Meyers, R.A. (ed.), 2012. Encyclopedia of sustainability science and technology.
Springer-Verlag, New York. https://doi.org/10.1007/978-1-4419-0851-3
Note that this encyclopedia is over 12000 pages.
Specifically, see the following entries
Solar irradiance, global distribution,
Solar radiation spectrum,
Solar radiation for solar energy utilization.
- https://en.wikipedia.org/w/index.php?title=Wien%27s_displacement_law&oldid=1161250340
- https://oeis.org/A094090
- https://oeis.org/A081819
- https://physics.nist.gov/cgi-bin/cuu/Value?bwien
- https://earthobservatory.nasa.gov/features/EnergyBalance,
archivebox
- https://en.wikipedia.org/w/index.php?title=Solar_irradiance&oldid=1162771845
- https://www.energy.gov/eere/solar/solar-radiation-basics,
archivebox
- https://solcast.com
chepec/photoec documentation built on July 27, 2023, 11:33 a.m.
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title: "The spectrum of a black body"
author: "Taha Ahmed"
date: "r Sys.Date()"
I made an attempt to to load siunitx in Rmd->HTML vignette -- it did not work, broke all LaTeX support
https://stackoverflow.com/a/55531382/1198249
output:
rmarkdown::html_vignette:
includes:
in_header: header.html
also tried header-includes, did not work (but without breaking all LaTeX)
header-includes:
- \usepackage{siunitx}
output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{The spectrum of a black body} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8}
library(dplyr) library(tidyr) # to use variables in dplyr::rename # https://stackoverflow.com/a/67644830/1198249 library(glue) library(stringr) # str_remove library(tibble) # add_column library(knitr) library(ggplot2) library(latex2exp) library(cowplot) library(ggrepel) library(gt) library(xtable) library(here) library(common)
options( digits = 7, width = 84, continue = " ", prompt = "> ", warn = 0, stringsAsFactors = FALSE) opts_chunk$set( dev = "svg", fig.align = "center", fig.width = 7.10, # 7.10/4.39=1.617 golden ratio # but we increase height slightly to make allowance for title, # secondary axis, caption, etc. fig.height = 4.58, echo = TRUE, eval = TRUE, cache = FALSE, collapse = TRUE, results = 'hide', message = FALSE, warning = FALSE, tidy = FALSE)
spectral.min <- 1E-7 # meter spectral.max <- 4E-6 # meter spectral.stepsize <- 1E-9 # meter vis.min <- 380e-9 # m vis.max <- 780e-9 # m
An ideal absorber absorbs all incident radiation and is called a black body. By simple conservation of energy, such a black body must then have an emissivity of unity. Every object at a temperature above 0 K emits and absorbs electromagnetic radiation to some degree. The the spectral distribution of a black body depends only on its temperature.
Stars are not ideal absorbers, but are to a very close approximation black bodies when considering their surface temperature.
The spectral radiance^[Irradiance is the radiant power emitted by the black body, and radiance is the radiant power received by another object. That is how these terms are usually defined in radiometry and how we use them in this package.] of a black body (i.e, its emitted power per unit area and per unit wavelength) at thermal equilibrium is given by Planck's law^[Planck's law describes the spectral radiance, $I$, of electromagnetic radiation at all wavelengths emitted in the normal direction from a black body in a cavity in thermodynamic equilibrium.]: \begin{equation} I\left(\lambda, T\right) = \frac{2{\pi}hc^2}{\lambda^5}\frac{1}{\exp\left(\displaystyle\frac{hc}{{\lambda}kT}\right) - 1} \end{equation} where $h$ is Planck's constant, $c$ is the speed of light in vacuum, and $k$ is Boltzmann's constant (please see table below for details on these constants). To be rigorous, we may note that when referring to a black body the spectral radiance is considered independent of viewing angle (isotropic), independent of time, and independent of position on the emitting surface (spatially homogeneous). Notice that in Planck's law the first term (the fifth-power term) has units of W m⁻² nm⁻¹ (assuming wavelength was given in nm) and that the second term (the exponential term) is unitless.
The amount of thermal radiation from a material can be determined by multiplying its spectral radiance and emissivity. For a black body the spectral radiance thus completely characterises its thermal output. This makes Planck's law very useful for modelling the solar radiance as well as the irradiance on Earth.
xtab.solarconstants <- photoec::solarconstants |> select(name, label.html, value, unit.html, reference) |> xtable::xtable() names(xtab.solarconstants) <- c("Name", "Symbol", "Value", "Unit", "Reference") # remember, digits() display() align() are length + 1 (include row.names) digits(xtab.solarconstants) <- c(0, 0, 0, 4, 0, 0) display(xtab.solarconstants) <- c("s", "s", "s", "e", "s", "s") align(xtab.solarconstants) <- c("l", "l", "c", "r", "l", "l") print( xtab.solarconstants, include.rownames = FALSE, # disabling sanitization is important to not mangle HTML markup inside the dataframe sanitize.text.function = function(x){x}, type = "html")
It is perhaps instructive to start off by modelling not just the Sun but also a higher- and a lower-temperature star using Planck's law.
surface.temperature <- c( # https://en.wikipedia.org/wiki/Gamma_Cassiopeiae # 25000, # K # https://en.wikipedia.org/wiki/Sirius # 9940, # K # https://en.wikipedia.org/wiki/Vega # 9602, # K # https://en.wikipedia.org/wiki/Fomalhaut # 8590, # K # https://en.wikipedia.org/wiki/Deneb 8525, # Sun filter(photoec::solarconstants, label=="T.Sun")$value, # https://en.wikipedia.org/wiki/Beta_Andromedae # 3842, # K # https://en.wikipedia.org/wiki/Betelgeuse 3600) bblong <- NULL for (i in 1:length(surface.temperature)) { bblong <- bind_rows( bblong, photoec::sunlight.Planck( wavelength = seq(spectral.min, spectral.max, spectral.stepsize), temperature = surface.temperature[i]) %>% # convert spectral radiance/irradiance columns from W m⁻² m⁻¹ to W m⁻² nm⁻¹ mutate(Sun.spectralradiance = 1e-9 * Sun.spectralradiance) %>% mutate(Earth.spectralirradiance = 1e-9 * Earth.spectralirradiance) %>% add_column(energy = photoec::wavelength2energy(.$wavelength), .after = "wavelength") %>% add_column(temperature = surface.temperature[i], .after = "energy") %>% pivot_longer( cols = !starts_with(c("wavelength", "energy", "temperature")), names_to = "property", values_to = "value")) }
In the above chunk we used Planck's law as implemented by our sunlight.Planck()
function to return spectral radiance as well as other derived quantities
for three different absolute temperatures.
# you want to be careful when extending the wavelength range towards larger values that # you don't use too large step sizes in the lower ranges, because that will mess up # the cumulative radiance values (due to trapezoidal integration) # NOTE that adding the two higher-wavelength ranges makes no discernible difference # to the calculated totals or visible range fractions wl.extended <- c(seq(1E-9, 2E-5, 1E-9), seq(3E-05, 1, 1E-4), seq(2, 1E6, 1E2)) radiances <- NULL for (i in 1:length(surface.temperature)) { radiances <- bind_rows( radiances, photoec::sunlight.Planck( wavelength = wl.extended, temperature = surface.temperature[i]) %>% add_column(temperature = surface.temperature[i], .after = "wavelength") %>% select(wavelength, temperature, Sun.radiance) %>% rename(total = Sun.radiance) %>% # find the total radiance (last value in vector, corresponds to largest wavelength) group_by(temperature) %>% slice_tail(n = 1) ) } # to avoid stupid errors due to temperatures possibly ordered differently, use join radiances <- left_join( radiances, bblong %>% group_by(temperature) %>% filter(property == "Sun.radiance") %>% # careful, this equals sign only works reliably if stepsize 1 nm filter(wavelength == vis.min) %>% # slice unnecessary if preceding comparison uses ==, but needed if we use > or < slice_head(n = 1) %>% select(temperature, value) %>% # dynamically construct new column name using glue notation # https://stackoverflow.com/a/67644830/1198249 rename("at{vis.min}" := value), by = "temperature") %>% left_join( bblong %>% group_by(temperature) %>% filter(property == "Sun.radiance") %>% filter(wavelength == vis.max) %>% slice_head(n = 1) %>% select(temperature, value) %>% rename("at{vis.max}" := value), by = "temperature") # radiance in the visible range # note the use of drop=TRUE to force return of vector and not tibble, which is otherwise the default # https://tibble.tidyverse.org/reference/subsetting.html radiances$visible <- radiances[, paste0("at", vis.max), drop=T] - radiances[, paste0("at", vis.min), drop=T] # fraction of radiance in the visible range compared to total radiance radiances$fraction <- radiances$visible / radiances$total
this.labeller <- setNames( # note that knitr device=svg throws lot of warnings when we used unicode # char (no-break space) instead of regular space character here # https://github.com/yihui/knitr/issues/496 paste0(unique(bblong$temperature), " K"), unique(bblong$temperature)) p.bb.spradiance <- ggplot(bblong %>% filter(property == "Sun.spectralradiance")) + facet_wrap( ~temperature, ncol = 1, scales = "free_y", labeller = as_labeller(this.labeller)) + # highlight visible spectrum range as area # would be really cool if we could colour this area as a rainbow... geom_ribbon( data = bblong %>% filter(property == "Sun.spectralradiance") %>% filter(wavelength >= vis.min & wavelength <= vis.max), fill = alpha("orange", 0.35), colour = NA, ymin = 0, aes(x = wavelength, ymax = value)) + geom_path( aes( x = wavelength, y = value)) + geom_text( data = radiances, x = mean(range(vis.min, vis.max)), # Y=Inf in combination with hjust=1 (note the angle) aligns the right-edge of the text # with top of plot area. hjust > 1 pushes the text downwards (also affected by textsize). y = Inf, hjust = 2.65, size = 3.25, # note that due to angle=90 here vjust affects horizontal positioning vjust = 0.5, angle = 90, colour = "#b36200", # dark orange aes( label = paste0(formatC(100 * fraction, digits=2), "%"), group = temperature)) + geom_label_repel( data = . %>% group_by(temperature) %>% filter(max(value) == value), size = 3.0, nudge_x = 1e-6, point.padding = unit(0.75, "lines"), arrow = arrow(length = unit(0.05, "npc")), aes( label = paste0(numbers2prefix(wavelength), "m"), x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Spectral radiance / kW m⁻² nm⁻¹", labels = rlang::as_function(~ 1e-3 * .)) + theme( legend.position = c(1, 1), legend.justification = c(1, 1)) p.bb.radiance <- ggplot(bblong %>% filter(property == "Sun.radiance")) + facet_wrap( ~temperature, ncol = 1, scales = "free_y", labeller = as_labeller(this.labeller)) + geom_ribbon( data = bblong %>% filter(property == "Sun.radiance") %>% filter(wavelength >= vis.min & wavelength <= vis.max), fill = alpha("orange", 0.35), colour = NA, ymin = 0, aes(x = wavelength, ymax = value)) + geom_path( aes( x = wavelength, y = value)) + geom_text( data = radiances, x = Inf, y = Inf, vjust = 2.25, hjust = 1.2, size = 3.25, aes( label = paste0(formatC(1E-6 * total, format="f", digits = 1), " MW m⁻²"), group = temperature)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Radiance / MW m⁻²", labels = rlang::as_function(~ 1e-6 * .)) + theme(legend.position = "none") title.cow <- ggdraw() + draw_label( "Black body spectra at three different temperatures", x = 0, hjust = 0, size = 14) + # manually adjusted title left-side margin to align with left plot panel theme(plot.margin = margin(0, 0, 0, 40)) subtitle.cow <- ggdraw() + draw_label( "Exemplified with Betelgeuse, the Sun, and Deneb. Visible range demarcated in yellow.", x = 0, hjust = 0, y = 1, size = 10) + # manually adjusted title left-side margin to align with left plot panel theme(plot.margin = margin(0, 0, 0, 40)) bb.row <- cowplot::plot_grid(p.bb.spradiance, p.bb.radiance, nrow = 1, rel_widths = c(1, 1)) cowplot::plot_grid(title.cow, subtitle.cow, bb.row, ncol = 1, rel_heights = c(0.1, 0.04, 1))
Visible range (r numbers2prefix(vis.min)m–r numbers2prefix(vis.max)m) shown as
a yellow area under both the spectral radiance and radiance curves, on the former
overlaid with the ratio of radiance in the visible range to the total radiance.
In the right-hand panels the total radiance (calculated by integrating spectral radiances over the
wavelength range r numbers2prefix(min(wl.extended))m–r numbers2prefix(max(wl.extended), digits = 4)m)
is also shown.
The shape of the spectral radiance curve (Planck's law) is only dependent on the temperature of the black body. The position of the peak of the spectral radiance shifts depending on the temperature (towards lower wavelengths for higher temperatures). The wavelength of the spectral radiance's maximimum can be deduced from the curve itself (i.e., Planck's law), or else from the so-called Wien displacement law, which is just another way to express the same thing: \begin{equation} \lambda_\mathrm{peak} = \frac{b}{T} \end{equation} where $T$ is the absolute temperature and $b$ is a proportionality constant ultimately derived from Planck's law: \begin{equation} b = \frac{hc}{xk} \approx 2.89777\ldots\cdot10^{-3} \mathrm{m~K} \end{equation} where $h$ is Planck's constant, $c$ is the speed of light, $k$ is Boltzmann's constant, and $x$ is a purely mathematical constant.^[$x$ is the positive solution to $x = 5(1 - \exp(-x))$, which is solved by $x = 5 + W(-5\exp(-5))$, where $W()$ is the Lambert W-function, and gives $x = 4.965114231744276\ldots$. But I must admit I don't know what the W-function is. Some function to wrangle this sort of exponential equation, I suppose.] Note that as parametrised here, the unit of $b$ is m K (that's metre Kelvin) and nothing else.
dflong <- photoec::sunlight.Planck(wavelength = wl.extended) %>% # convert spectral radiance/irradiance columns from W m⁻² m⁻¹ to W m⁻² nm⁻¹ mutate(Sun.spectralradiance = 1e-9 * Sun.spectralradiance) %>% mutate(Earth.spectralirradiance = 1e-9 * Earth.spectralirradiance) %>% # the use of .$ notation was necessary here (because inside function call, I guess) add_column(energy = photoec::wavelength2energy(.$wavelength), .after = "wavelength") %>% # transform dataframe to long format (better suited for tidy and gpplot2) pivot_longer( cols = !starts_with(c("wavelength", "energy")), names_to = "property", values_to = "value") dflong %>% glimpse()
# using facetting is not suitable because we have different y-axis for every plot... p.sun.spradiance <- ggplot(dflong %>% filter(property == "Sun.spectralradiance") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max)) + geom_line( aes( x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Sp. radiance / kW m⁻² nm⁻¹", labels = rlang::as_function(~ 1e-3 * .)) + theme(legend.position = "none") p.sun.radiance <- ggplot(dflong %>% filter(property == "Sun.radiance") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max)) + geom_line( aes( x = wavelength, y = value)) + geom_text( # cannot use . here, must be explicit, otherwise we get the data truncated # at vis.max whereas we want the radiance for the extended spectral range data = dflong %>% filter(property == "Sun.radiance") %>% slice_tail(n = 1), x = Inf, y = Inf, vjust = 2.50, hjust = 1.2, size = 3.25, aes(label = paste0(formatC(1E-6 * value, format = "f", digits = 1), " MW m⁻²"))) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Radiance / MW m⁻²", labels = rlang::as_function(~ 1e-6 * .)) + theme(legend.position = "none") p.sun.luminosity <- ggplot(dflong %>% filter(property == "Sun.luminosity") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max)) + geom_line(aes(x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous(name = "Luminosity/W") + theme(legend.position = "none") ## p.earth.spirr <- ggplot(dflong %>% filter(property == "Earth.spectralirradiance") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max)) + geom_line( aes( x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous(name = "Sp. irradiance / W m⁻² nm⁻¹") + theme(legend.position = "none") p.earth.irr <- ggplot(dflong %>% filter(property == "Earth.irradiance") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max)) + geom_line( aes( x = wavelength, y = value)) + geom_text( # cannot use . here, must be explicit, otherwise we get the data truncated # at vis.max whereas we want the irradiance for the extended spectral range data = dflong %>% filter(property == "Earth.irradiance") %>% slice_tail(n = 1), x = Inf, y = Inf, vjust = 2.50, hjust = 1.2, size = 3.25, aes(label = paste0(formatC(value, format = "f", digits = 1), " W m⁻²"))) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Irradiance / kW m⁻²", labels = rlang::as_function(~ 1e-3 * .)) + theme(legend.position = "none") p.earth.luminosity <- ggplot(dflong %>% filter(property == "Earth.luminosity") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max)) + geom_line(aes(x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous(name = "Luminosity/W") + theme(legend.position = "none") # https://datavizpyr.com/join-multiple-plots-with-cowplot/ title.cow <- ggdraw() + draw_label( paste0( "Spectrum of the Sun modelled as a black body (", paste0(1e9 * spectral.min, " nm"), # en dash "–", paste0(1e6 * spectral.max, " µm"), ")"), x = 0, hjust = 0, size = 14) + # manually adjusted title left-side margin to align with left plot panel theme(plot.margin = margin(0, 0, 0, 45)) title.sun <- ggdraw() + draw_label("Solar radiance", angle=-90, x=0.5, y=0, hjust=1.65, vjust=0.5, size=12) # hjust adjust up/down position of right-side labels and was adjusted manually title.earth <- ggdraw() + draw_label("Irradiance on Earth", angle=-90, x=0.5, y=0, hjust=1.37, vjust=0.5, size=12) row.sun <- cowplot::plot_grid(p.sun.spradiance, p.sun.radiance, title.sun, nrow = 1, rel_widths = c(1, 1, 0.1), labels = c("a", "b"), label_x = 0.16, label_y = 0.97) row.earth <- cowplot::plot_grid(p.earth.spirr, p.earth.irr, title.earth, nrow = 1, rel_widths = c(1, 1, 0.1), labels = c("c", "d"), label_x = 0.16, label_y = 0.97) cowplot::plot_grid(title.cow, row.sun, row.earth, ncol = 1, rel_heights = c(0.1, 1, 1))
Figure above shows the spectral radiance and radiance of the Sun
and the spectral irradiance and radiance at Earth's surface
(note that at this level of abstraction the thickness of
the atmosphere is all but irrelevant).
Note that just as earlier the displayed total radiance values (in the right-hand panels)
are based on the extended wavelength range
r numbers2prefix(min(wl.extended))m–r numbers2prefix(max(wl.extended), digits = 4)m.^[By
taking a wider wavelength range into account we get a better approximation of the total radiance.
For example calculating the total irradiance on Earth when limited to the plotted wavelength range
yields a value of
r dflong %>% filter(property == "Earth.irradiance") %>% filter(wavelength >= spectral.min & wavelength <= spectral.max) %>% slice_tail(n=1) %>% pull(value) %>% formatC(digits=1, format="f") W m⁻².]
Let's take a closer look at the two terms in Planck's law, i.e., the power term and the exponential term. Both terms vary with many orders of magnitude over the solar spectral range which makes them awkward to plot, so instead we will look at their values at the spectral range extremes.
The power-term goes from
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(wavelength) %>% numbers2prefix()m
to
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(wavelength) %>% numbers2prefix()m,
i.e., a difference of eight orders of magnitude.
Notice how it goes from extremely large values at low wavelength to very large values
at long wavelengths. But it does continue dropping (as power laws do, asymptotically towards
zero) so that by a wavelength of 1 m it is 1e-16 W m⁻² nm⁻¹ and four orders of magnitude later
(i.e, at a wavelength of 10 km) it is 1e-36 W m⁻² nm⁻¹ (20 orders of magnitude smaller).
dflong %>% filter(property == "Sun.spectralradiance.powerterm") %>% head() dflong %>% filter(property == "Sun.spectralradiance.powerterm") %>% tail()
The exponential term goes from
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_head(n=1) %>% pull(wavelength) %>% numbers2prefix()m
to
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(value) %>% numbers2prefix()W m⁻² nm⁻¹
at
r bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value) %>% slice_tail(n=1) %>% pull(wavelength) %>% numbers2prefix()m,
i.e., a difference of 11 orders of magnitude.
dflong %>% filter(property == "Sun.spectralradiance.expterm") %>% head() dflong %>% filter(property == "Sun.spectralradiance.expterm") %>% tail()
From the above results we can see that the powerterm drops much faster than the exponential rises, giving us the spectral radiance curve that slowly drops to almost zero at high wavelengths. And despite the powerterm growing towards lower wavelengths, it is still outmatched by the much stronger drop in the exponential (which in fact goes to zero), giving the spectral radiance curve that drops quickly towards zero at the lowest wavelengths.
In fact, the spectral radiance goes above 1e-30 W m⁻² nm⁻¹ only by a wavelength of 25 nm, and above 1 µW m⁻² nm⁻¹ only at wavelengths above 62 nm. As we saw the slope is less extreme towards higher wavelengths. By 530 µm the spectral radiance has dropped to the microwatt level again, but does not drop to around 1e-30 W m⁻² nm⁻¹ until a wavelength of around 400 m (yes, that's meters).
So based purely on Planck's law, in order to estimate the Sun's black body total
radiant power to a high degree of accuracy, we should use a wavelength range from
at least 25 nm to 400 m.
Note that for estimating total radiant power not only the spectral radiance,
but also the spectral flux matters. That is, despite high-energy gamma rays being
extremely energetic (wavelengths down to $10^{-17}$ nm or
r common::numbers2prefix(photoec::wavelength2energy(1e-17))eV which is beyond
even our most powerful particle accelerators, I believe) the amount of such
photons is effectively zero, as we saw above.
Note that the total radiant power values given in the plots above integrated
radiance over an even wider wavelength range,
r numbers2prefix(min(wl.extended))m–r numbers2prefix(max(wl.extended), digits = 4)m.
# 3.74e19 W m⁻² nm⁻¹ at 1 nm, drops to 3.654e11 at 4000 nm (8 orders of magnitude) p <- ggplot(data = bblong %>% filter(property == "Sun.spectralradiance.powerterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value)) + coord_cartesian(y = c(0, 1e13)) + geom_line( aes( x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Spectral radiance / W m⁻² nm⁻¹") + # labels = rlang::as_function(~ 1e-6 * .)) + theme(legend.position = "none") # 1.49e-11 W m⁻² nm⁻¹ at 1 nm, rises to 1.16 at 4000 nm (11 orders of magnitude) ggplot(data = bblong %>% filter(property == "Sun.spectralradiance.expterm") %>% filter(temperature == filter(solarconstants, label == "T.Sun")$value)) + # coord_cartesian(y = c(0, 1e13)) + geom_line( aes( x = wavelength, y = value)) + scale_x_continuous( name = "Wavelength / nm", labels = rlang::as_function(~ 1e9 * .)) + scale_y_continuous( name = "Spectral radiance / W m⁻² nm⁻¹", sec.axis = dup_axis()) + # labels = rlang::as_function(~ 1e-6 * .)) + theme(legend.position = "none")
We should perhaps mention how we calculate the irradiance on Earth from the solar
radiance values. The distance between the Earth and the Sun varies over the year,
but for our purposes the astronomical unit has sufficient precision.
We assume the solar radiance (power per unit area) is spread evenly across the entire
surface of the Sun (isotropic radiation), and since the Earth radius is tiny compared
to the Sun and the distance between them is huge only a miniscule fraction of the
solar radiance can impinge on the planet.
We can calculate this fraction by a little geometry: consider two spheres centered on
the Sun, one with a radius equal to the Sun, and the other with a radius of Earth's
orbit (i.e., 1 AU). The fraction we seek (or in other words an attenuation factor) is
the squared quotient of the inner sphere's radius to the outer sphere's radius,
$R_\mathrm{Sun}/R_\mathrm{Earth}$ =
r (filter(photoec::solarconstants, label=="R.Sun")$value / filter(photoec::solarconstants, label=="R.AU")$value)^2 %>% formatC(format="e", digits=2).
You may have already noticed that this geometric argument is just another way to express
the inverse square law:
\begin{equation}
I_\mathrm{Earth} = I_\mathrm{Sun} \frac{4\pi R_\mathrm{Sun}^2}{4\pi R_\mathrm{Earth}^2} =
I_\mathrm{Sun} \left(\frac{R_\mathrm{Sun}}{R_\mathrm{Earth}}\right)^2
\end{equation}
Sources
- Nilsson, A.M., 2012. Daylighting systems: development of techniques for optical characterization and performance evaluation (PhD thesis). Uppsala university, Uppsala.
- Bayrak Pehlivan, I., 2013. Functionalization of polymer electrolytes for electrochromic windows (PhD thesis). Uppsala university, Uppsala.
- Meyers, R.A. (ed.), 2012. Encyclopedia of sustainability science and technology. Springer-Verlag, New York. https://doi.org/10.1007/978-1-4419-0851-3 Note that this encyclopedia is over 12000 pages. Specifically, see the following entries Solar irradiance, global distribution, Solar radiation spectrum, Solar radiation for solar energy utilization.
- https://en.wikipedia.org/w/index.php?title=Wien%27s_displacement_law&oldid=1161250340
- https://oeis.org/A094090
- https://oeis.org/A081819
- https://physics.nist.gov/cgi-bin/cuu/Value?bwien
- https://earthobservatory.nasa.gov/features/EnergyBalance, archivebox
- https://en.wikipedia.org/w/index.php?title=Solar_irradiance&oldid=1162771845
- https://www.energy.gov/eere/solar/solar-radiation-basics, archivebox
- https://solcast.com
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