The TROPOspheric Monitoring Instrument (TROPOMI) is the only payload of the
Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of
the European Space Agency (ESA). TROPOMI is a nadir-viewing spectrometer
measuring in the ultraviolet, visible, near-infrared, and the shortwave
infrared that provides near-global daily coverage. Among other things,
TROPOMI measurements will be used for calculating the UV radiation reaching
the Earth's surface. Thus, the TROPOMI surface UV product will contribute to
the monitoring of UV radiation by providing daily information on the
prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on
the heritage of the Ozone Monitoring Instrument (OMI) and the Satellite
Application Facility for Atmospheric Composition and UV Radiation (AC SAF)
algorithms. This paper provides a description of the algorithm that will be
used for estimating surface UV radiation from TROPOMI observations. The
TROPOMI surface UV product includes the following UV quantities: the UV
irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV;
and the vitamin-D weighted UV. Each of these are available as (i) daily dose or
daily accumulated irradiance, (ii) overpass dose rate or irradiance, and
(iii) local noon dose rate or irradiance. In addition, all quantities are
available corresponding to actual cloud conditions and as clear-sky values,
which otherwise correspond to the same conditions but assume a cloud-free
atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm
has been tested using input based on OMI and the Global Ozone Monitoring
Experiment-2 (GOME-2) satellite measurements. These preliminary results
indicate that the algorithm is functioning according to expectations.
Introduction
Solar ultraviolet (UV) radiation has a broad range of effects concerning life
on Earth. Because of its high photon energy, UV radiation influences human
health, terrestrial and aquatic ecosystems, air quality, and materials in
various ways. For a more detailed discussion on the different effects of UV
radiation, see, e.g. . In order to study and assess these
effects and their implications thoroughly, information is needed on the
geographical and temporal distribution of UV radiation reaching the Earth's
surface.
After the discovery of severe ozone depletion in Antarctica during the
austral spring , it was soon recognized that the
stratospheric ozone content was also declining in the Arctic and at
midlatitudes . Subsequently, the UV radiation reaching the
Earth's surface increased during the last decades of the 20th century, as
documented in . The report further found that the strongest
increase took place in the high latitudes of the Southern Hemisphere, while
the Arctic and midlatitudes in both hemispheres have also experienced UV
increases. Outside the polar regions, the increase has been mostly around
5 % or less compared to pre-industrial conditions, whereas at high
and polar latitudes, where ozone depletion has been larger, increases have
been more substantial .
Thanks to the Montreal Protocol , concentrations of ozone-depleting substances in the stratosphere are currently decreasing and the
total ozone column is on a recovery path back towards pre-1980 levels, which
are expected to be reached before the middle of the 21st century
. Here, it is worth noting that factors other than the
ozone column, for example clouds and surface albedo, also play an important
role in determining how much UV radiation reaches the Earth's surface. Current
projections of the future UV radiation climate indeed bring forth the complex
connections between climate change, stratospheric ozone depletion, and
stratospheric dynamics, which all influence the UV radiation of our future
climate . Thus, it is of great importance to continue
monitoring the UV radiation reaching the Earth's surface.
The Sentinel-5 Precursor (S5P) is a polar-orbiting satellite mission,
launched on 13 October 2017. The only payload of the mission is the
TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing
push-broom-type imaging spectrometer measuring in the ultraviolet, visible,
near-infrared, and the shortwave infrared. The S5P mission is on
a sun-synchronous orbit with an ascending node equatorial crossing at 13:30,
which in conjunction with a wide swath of 2600 km provides
near-global daily coverage. TROPOMI measures radiation backscattered from the
Earth–atmosphere system. Among other things, TROPOMI measurements will be
used for calculating the UV radiation reaching the Earth's surface over the
sunlit part of the globe. Thus, the TROPOMI surface UV product will
contribute to monitoring UV radiation by providing daily
information on the prevailing UV conditions over the globe.
This paper provides a description of the algorithm that will be used for
estimating surface UV radiation from TROPOMI observations, including
a discussion on algorithm heritage and some example results based on
currently active satellite instruments.
Heritage
The method by is one of the first satellite-based algorithms
for estimating UV irradiances at the Earth's surface presented in the literature.
Their method is based on measurements of backscattered UV radiation taken by the
Total Ozone Mapping Spectrometer (TOMS) instrument. The general idea in their
approach is to first calculate clear-sky UV irradiances, taking into account
the total ozone column retrieved from measurements taken by the same instrument,
and then in a second step correct these clear-sky irradiances for the
attenuation caused by clouds. The cloud effect is determined based on the
Lambertian equivalent reflectance (LER) at 360 or 380 nm, which is
a measure of how reflective the clouds are. The higher the reflectance, the
thicker the cloud (optically) and thus the attenuation of
the surface UV irradiance caused by this cloud is stronger. This relationship has later
been refined to also take into account the effect of
multiple scattering between the surface and the cloud see
also, yielding the following expression:
CT=(1-LER)/(1-RG)
where RG is the LER value representing the surface (that is, LER at
cloud-free conditions), and CT is the cloud correction
or cloud transmittance
factor, which is also commonly referred to as the cloud modification factor
(CMF) . This factor is applied to
the clear-sky UV irradiance (Eclear) to obtain an estimate of the
UV irradiance under the cloud (E):
E=Eclear⋅CMF=Eclear⋅CT.
Many satellite UV algorithms presented after the pioneering work of
inherits their method. However, it is worth noting that, in the TOMS UV algorithm,
Eck's LER method was replaced with a more realistic plane parallel cloud model at the turn
of the century . In the plane parallel cloud model, the cloud
optical depth is estimated using radiative transfer calculations assuming a plane parallel water
cloud, and given as input to the measured reflectance. The advantage of this approach is that it describes
more realistically the wavelength-dependent attenuation of incoming solar
radiation by clouds and also that it
accounts for the directional distribution of radiation reflected off the
cloud.
The Dutch–Finnish Ozone Monitoring Instrument (OMI) on board NASA's Aura
satellite launched in 2004 continues the TOMS UV record to the present. The
OMI UV algorithm is, in essence, very similar to that
of TOMS. A recent update of the OMI UV algorithm added climatological aerosol
information in order to account for the attenuation caused by absorbing
aerosols .
For estimating daily UV exposure or daily doses, a disadvantage of the
above-described TOMS branch of satellite UV algorithms is that they are based
on only one satellite overpass per day. This means that the algorithm does
not account for variations in cloudiness that occur within a day.
Instead the cloud situation of the overpass is assumed to be valid for the
whole day. Therefore, days with varying cloud conditions cause a larger
uncertainty in the daily UV doses .
Another approach for estimating surface UV irradiances from satellite
measurements is to use cloud information from geostationary satellites in
combination with total ozone column from polar-orbiting platforms. This
approach has the advantage of having almost continuous cloud observations,
but, on the other hand, is not able to cover high-latitudes because of
challenging view angles. Geostationary satellite UV algorithms have been
developed for both the European and North American regions
.
In order to gain a better picture of the intra-day cloud variability, some
algorithms utilize measurements from multiple polar-orbiting satellites
. This approach is also used
in the offline UV (OUV) product provided by EUMETSAT's
Satellite Application Facility for Atmospheric Composition and UV Radiation
(AC SAF; formerly known as the Ozone and Atmospheric Chemistry Monitoring
Satellite Application Facility). The OUV algorithm utilizes cloud
measurements taken by Advanced Very High Resolution Radiometer (AVHRR)
instruments and carried by two different polar-orbiting satellites (Metop and
NOAA POES) to produce a global gridded daily UV product (level 3 product). In
the OUV algorithm, the total ozone column is taken from GOME-2.
As explained in more detail in Sect. 3, the approach chosen for estimating
surface UV irradiances based on TROPOMI measurements builds on the TOMS-OMI
heritage, while also utilizing parts of the AC SAF OUV algorithm. Radiative
transfer calculations and look-up table (LUT) functionality of the TROPOMI UV
algorithm are based on the AC SAF OUV algorithm, while other parts of the
algorithm are mostly based on OMI. One exception here is that the TROPOMI UV
algorithm uses the reflectance at 354 nm, while OMI uses that at
360 nm, for calculating the cloud optical depth. Furthermore, the
surface albedo climatology used in TROPOMI is an improved version of that
used in OMI, following the approach chosen in AC SAF OUV.
In practice, the TROPOMI UV algorithm estimates the surface UV using
radiative transfer calculations implemented in a LUT to keep computational
demands at a reasonable level. The inputs for these radiative transfer
calculations are essentially the TROPOMI-retrieved total ozone column and
reflectance at 354 nm, together with information on the surface albedo
and the atmospheric aerosol load taken from other sources.
Of the above-discussed heritage UV products, the TOMS UV record is the
longest. The TOMS UV record is based on measurements taken by a series of
satellites. It begins with measurements taken by the Nimbus 7 satellite in 1978 and
ends with the Earth Probe in 2007.
The major TOMS instruments flew on
orbits with a 12:00 equator crossing time, while OMI and TROPOMI has
equator crossing times of 13:45 and 13:30, respectively. The OMI UV product
covers the years from 2004 to the present and is currently foreseen to last for
at least a few more years, while TROPOMI will continue this satellite UV
record further into the future. Thus, there will most probably be at least
some years of overlap between TROPOMI and OMI. This overlap will be very
useful for validation purposes and time series analyses. Although the AC SAF
OUV comprises a somewhat different type of UV product (because it is a direct
L3 product), it is worth noting that the OUV record covers the period
from 2007 onwards, and thus will also be available for comparison with the
TROPOMI UV product.
TROPOMI surface UV algorithm
For the TROPOMI UV algorithm, we have chosen to use the VLIDORT radiative
transfer model . VLIDORT is a vector discrete ordinate
radiative transfer model that accounts for polarization. It has been used,
for example, in the satellite UV algorithm of AC SAF .
The inputs to the VLIDORT radiative transfer calculations are essentially the
total ozone column (Ω), the surface albedo (ρs), and
the cloud optical depth (τc). Based on these, the UV
irradiances at the Earth's surface are calculated through a LUT-based approach,
which reduces the computational demands compared to online radiative
transfer model calculations. Here, the total ozone column is a retrieved L2
product of TROPOMI, available in the Total Ozone product ,
while the cloud optical depth is estimated as part of the UV algorithm (see
Sect. 3.3) based on the measured reflectance at 354 nm (R354)
provided by the L2 aerosol index (AI) product .
Figure presents a schematic flow diagram of the TROPOMI UV
algorithm. In practice, the TROPOMI UV algorithm uses two sets of LUTs
instead of explicitly running the radiative transfer model. One LUT gives
τc using R354 and ρs as main inputs,
while the other one gives the UV irradiance using Ω,
τc, and ρs as main inputs. Here,
ρs is taken from a climatology created for the OUV
algorithm. It uses the monthly minimum Lambert equivalent reflectivity (MLER)
climatology for regions and time periods with permanent
or negligible snow/ice cover, while a climatology better capturing the
seasonal changes in the surface albedo during the
transition periods is used elsewhere (see for
details). A correction for the effect of absorbing aerosols corresponding to
climatological aerosol properties is applied, following the OMI aerosol
correction approach .
In the following subsections, we first briefly discuss the influence of various
factors such as clouds and aerosols have on surface UV irradiances.
Thereafter, we describe the approach used in the radiative transfer model
within the TROPOMI UV algorithm, including a description of how the LUTs are
implemented.
Schematic flow chart of the TROPOMI UV algorithm. See text for details.
Factors affecting surface UV
The UV irradiance at the Earth's surface is largely determined by the solar
zenith angle, clouds, total ozone column, surface albedo, aerosols, Earth–Sun
distance, and altitude or pressure. The different factors affecting surface
UV radiation have been discussed in the literature (see, e.g.
, and reference therein). Here, we only include a brief
discussion of these factors and encourage the interested reader to study the
literature more in depth.
Solar zenith angle
The solar zenith angle (θ0) determines
the optical path of the direct radiation component through the atmosphere and
is therefore the most important factor for the surface UV irradiance. Through
its influence on the optical path, the solar zenith angle modifies the effect
that other factors have on the surface UV. The smaller the solar zenith angle
(higher sun), the more UV radiation reaches the surface, and vice versa.
Clouds
Clouds attenuate UV radiation in a way which is similar to
the familiar attenuation of visible radiation under cloudy skies: they
reflect part of the incoming radiation back to space, thereby reducing the
irradiance reaching the Earth's surface. found an average
CMF (cloud modification factor) of 0.4 for overcast conditions at a Swedish
station, with fairly large variation in the observed CMF values around this
average, depending on the detailed properties of the prevailing cloud. For
cloud amounts less than 4 out of 8 (octas), Josefsson and Landelius found a CMF
larger than 0.9, indicating that UV radiation is only weakly attenuated as
long as less than half of the sky is covered by clouds. Den Outer et al. (2005)
found a climatological yearly average CMF of 0.68 for erythemal UV in the
Netherlands, while for global solar radiation (integrated over the wavelength
range 300–3000 nm), they found a climatological CMF of 0.57. Thus,
there is a wavelength dependence in the attenuation of incoming solar
radiation by clouds, with radiation of shorter wavelengths making it to the
surface more effectively. The physical aspects of this effect have been
discussed by .
In radiative transfer, the cloud optical depth (τc) is often
used as a measure of the opacity of the cloud. τc defines
how much a beam of radiation passing through the cloud is attenuated,
following the Beer–Lambert–Bouguer law.
Although clouds generally attenuate the UV radiation reaching the surface, it
is worth noting that, in certain conditions, they can also act to
intermittently increase the surface UV irradiance to above what would be
expected in otherwise equivalent but cloud-free conditions. When the sun is
not obscured by clouds, they can act as reflecting surfaces enhancing the UV
irradiance reaching the surface e.g..
Total ozone column
The total ozone column (Ω) is
predominantly a measure of the ozone content of the stratosphere, because
most of the ozone of the atmosphere resides there. As ozone strongly absorbs
UV radiation at wavelengths below 320 nm, the stratospheric ozone
layer protects life on Earth from too intense UV radiation. Variations in the
total ozone column are reflected in the UV irradiances at the surface. The
larger the total ozone column, the lower the UV irradiance and vice versa.
The exact relationship between total ozone and surface UV depends on the
wavelength considered and also on the total ozone column and the solar
zenith angle. For erythemally weighted UV and moderate to high sun
(θ0<60∘), a 1 % change in the total ozone column
leads roughly to a 1–1.2 % change in the UV .
Albedo
The surface UV albedo (ρs) is generally
low, being of the order of 0.05 for most surfaces, as shown, for example, by
the TOMS satellite data . Surfaces covered by snow or ice,
however, exhibit much higher surface albedos
. A high surface albedo may enhance the UV
level at the surface significantly due to multiple scattering between the
surface and the atmosphere above. It has been shown, for example, that
a surface covered by fresh and clean snow (albedo 0.8) enhances the UV
irradiance at 320 nm by a factor of 1.5 compared to snow-free, low
albedo conditions .
The UV irradiance at a specific location is not only influenced by the local
surface albedo at the measurement site, but also by the often inhomogeneous
surface conditions of the surrounding area, extending a few tens of kilometres
away from the measurement site . The
effect of the varying surface conditions in the surroundings of the
measurement site can be represented by the effective albedo. The
effective surface albedo can be thought of as the albedo required in
a one-dimensional radiative transfer model in order to produce a cloud-free
UV irradiance that is in agreement with measurements.
Aerosols
Aerosols usually decrease the level of UV radiation
reaching the surface, partly by scattering radiation back to space and partly
by absorption. The aerosol load of the atmosphere varies strongly in time and
space. Therefore, the effect of aerosols on the UV irradiance reaching the
surface also shows strong variation. During a measurement campaign in Greece
in 1996, aerosols were found to decrease the UV irradiance by
5–35 % compared to aerosol-free conditions .
These numbers are similar to the yearly average aerosol attenuation in
various parts of the globe corresponding to the aerosol correction applied in
the OMI UV algorithm . This correction is based on the
aerosol absorption optical depth (τaa) and will also be used
in the TROPOMI UV algorithm (see Sect. 3.5).
Altitude
The UV irradiance at the surface usually increases with
increasing altitude (z) . This is due to the fact that
the surface pressure (ps) is smaller at higher altitude. In
other words, there is less atmosphere at high altitudes, and therefore
less scattering and absorption takes place. Moreover, tropospheric ozone is
mostly located at low altitudes, which is also the case for other pollutants
such as aerosols. At high altitudes there are also typically less clouds, or
even clouds beneath acting as a reflecting surface with high albedo, thus
increasing the UV irradiance compared to less elevated sites.
Earth–Sun distance
The Earth–Sun distance (R) varies over the
course of the year because of the elliptic shape of the Earth's orbit around the
Sun. Because of this variation, the irradiance at the top of the atmosphere
varies as a function of 1/R2. This variation, which is of the order of
±3%, can be taken into account using a multiplicative factor to
irradiances representing the baseline Earth–Sun distance of 1 AU.
General radiative transfer set-up
The aim of the radiative transfer set-up of the TROPOMI UV algorithm is to
account for the factors influencing the surface UV irradiance discussed
above. VLIDORT is a one-dimensional radiative transfer model where the
vertical structure of the atmosphere is represented by 30 model layers, as
depicted in Fig. . At the very bottom, there is a
surface, which in our set-up is a Lambertian reflector characterized by its
albedo. The layer 1–2 km above the surface (layer 2) includes
a homogeneous water cloud. In addition, all layers include Rayleigh
scattering by air molecules (p is the pressure), absorption by ozone, and
temperature information.
The cloud (layer 2) consists of water droplets with a size distribution
following the C1 model by yielding an effective
cloud droplet radius of reff=6µm. The same cloud
model has been used in the TOMS–OMI and the AC SAF UV algorithms
.
The temperature and the ozone density of each layer in the radiative transfer
model is set according to the TOMS V7 climatology ,
which gives climatological ozone and temperature profiles for three broad
latitude bands (low latitude, midlatitude, and high latitude) as
a function of total ozone column.
This general set-up of the VLIDORT model is used for both (i) calculating the
cloud optical depth and (ii) calculating surface UV irradiances, as
described in the following subsections. All radiative transfer calculations
were done using the extraterrestrial solar spectrum of OMI
and assuming an Earth–Sun distance of 1 AU.
Schematic structure of the model atmosphere.
Node points of the cloud optical depth look-up table.
Cloud optical depth vs. the reflectance at 354 nm according to the
look-up table. For the relationship shown here, the surface pressure was
ps=1atm and the solar and viewing geometry was
θv=40∘, θ0=45∘, and
ϕr=60∘.
Node points of the look-up table for the dose rates and UV irradiances at
selected wavelengths. The full 26 profile set of the TOMS V7 climatology is
used. L, M, and H refer to the low-, middle-,
and high-latitude profiles, respectively, while the numbers refer to total ozone columns in DU.
The main input used to estimate the cloud optical depth (τc)
is the reflectance at 354 nm (R354). R354 is available in
the TROPOMI AI L2 output, as it is also used for calculating the aerosol
index. R354 is defined as their Eq. 4-1:
R354=πI354E0,354cos(θ0),
where I354 is the radiance at 354 nm reflected by the Earth
(atmosphere and surface) measured by TROPOMI and E0,354 is the solar
irradiance at 354 nm at the top of the atmosphere, and θ0 is
the solar zenith angle. E0,354 is measured by TROPOMI on a daily
basis and is corrected for the Doppler shift in the measured spectrum due to
the relative motion of the satellite with respect to the Sun. Both I354
and E0,354 are the average over five consecutive spectral pixels centred
at 354 nm of the TROPOMI instrument. Furthermore, they have both been
normalized to correspond to an Earth–Sun distance of 1 AU.
In our radiative transfer calculations, the combined spectral response of
these five consecutive pixels are represented by a 0.88 nm wide
(corresponding to 5 pixels 0.22 nm apart), flat-top slit
function with Gaussian tails, which have a width of 0.27 nm at half
maximum.
The approach here is somewhat different from that used in the OMI UV
algorithm, where the radiance of a single spectral pixel at 360 nm is
used to determine the reflectance, from which the cloud optical depth is
consecutively calculated. We believe the approach chosen for TROPOMI will
constitute an improvement because (i) averaging over five channels will help
reduce noise in the signal, and (ii) while there is some O2-O2
absorption at 360 nm that may influence the
estimated cloud optical depth, 354 nm is free of such absorption
features.
The cloud LUT was calculated using the VLIDORT radiative transfer model.
R354 was calculated by systematically varying the cloud optical depth
(τc), the solar zenith angle (θ0), the viewing
zenith angle (θv), the relative azimuth angle
(ϕr) between the sun and the satellite, the surface albedo
(ρs), and the surface pressure (ps). The
outcome is a look-up table spanning all relevant combinations of these
parameters that gives τc as a function of the other
parameters by interpolating in the multidimensional space defined by the LUT
nodes. Interpolation is performed using polynomial (Lagrangian)
interpolation. The base alternative is to use 4 points from the surrounding
space, resulting in third-degree polynomial interpolation. If the desired point
is close to the boundary of the LUT, then 3 points are used (resulting in second-degree polynomial interpolation), while for points outside the LUT space, 2
points are used (linear extrapolation). The same interpolation scheme is also used
for the UV LUT (Sect. 3.4).
Note that here τc is an effective optical depth in the sense
that it corresponds to the cloud optical depth of a homogeneous water cloud,
as specified above, that produces the best match with the measured R354
given the other input parameters. Note that the ozone content of the
atmosphere has a negligible influence on R354. Therefore, we used
a constant ozone profile in these calculations, corresponding to the midlatitude TOMS V7 profile with a total ozone column of 325 DU (i.e.
M325 in Table ).
The nodes of the cloud LUT are listed in Table . All inputs
needed to retrieve τc are based on the TROPOMI AI L2 output,
except the albedo, which is based on a climatology as explained above.
ps of the AI L2 output is normally based on the pressure fields
of the European Centre for Medium-Range Weather Forecasts (ECMWF). In the case of
missing data from the ECMWF, ps is calculated from the altitude
a.s.l. using the hydrostatic equation and assuming a scale height of
8.3 km. The altitude in the AI L2 output is based on Global
Multi-resolution Terrain Elevation Data 2010 .
To demonstrate the idea of estimating τc based on the
measured R354, Fig. shows τc as
a function of R354 for a low albedo (ρs=0.04) and
a fairly high albedo (ρs=0.60) case. For the low-albedo
case, R354 increases strongly with increasing τc up to
optical depths of around 20, whereafter the increase gradually levels off as
R354 saturates towards large τc. Note that for the high-albedo case, R354 is less sensitive to changes in τc
than for the low-albedo case. This means, in practice, that it is more
difficult to accurately estimate τc for high-albedo cases.
Finally, the figure also brings forth the strong Rayleigh scattering of
radiation in the UV; for cloudless skies (τc=0), the low
albedo R354 is around 0.25.
UV LUT
The solar irradiance at Earth's surface is a function of wavelength.
Furthermore, the effect of the incoming radiation on, for example, a specific
photochemical reaction or a biological response, depends on the wavelength.
In order to quantify the effectiveness of radiation with respect to
a specific effect, various action spectra (weighting functions) have been
introduced e.g. that can be used to calculate
effective spectral irradiances and dose rates
e.g.Eq. 2.
The UV LUT of the TROPOMI algorithm includes UV irradiances at four selected
wavelengths, namely 305, 310, 324, and 380 nm, and erythemally
and vitamin-D weighted UV dose rates the tabulated
data provided in the publication were linearly interpolated to obtain
a complete action spectrum. Note that both the erythemal and the
vitamin-D action spectrum gives large weight to radiation of wavelengths
below 320 nmsee Fig. 3 in.
Similarly to the cloud LUT, the LUT for UV irradiances and dose rates was
created by running the radiative transfer model by systematically varying the
following input parameters: θ0, Ω, τc,
ρs, and ps. Table lists the
nodes chosen for the UV LUT. Here, the ozone profile follows the TOMS V7
climatology as explained above.
For comparison with ground-based measurements of UV irradiances, it is
worth noting that all calculations for the UV LUT were done using
a triangular 1 nm full-width-at-half-maximum (FWHM) slit function, which
is commonly used as a standard slit function, for example, when comparing
different ground-based spectrometers . Note also that the
wavelengths of the extraterrestrial spectrum used in our radiative transfer
calculations have been corrected to correspond to
wavelengths in the atmosphere rather than in a vacuum.
The reflectance at 354 nm(a), the cloud optical depth (b), and the UV index at solar noon (c) of the TROPOMI UV
algorithm based on OMI test data for 13 August 2007. Jokioinen (south-western
Finland) and Sodankylä (northern Finland) are marked with black squares.
Daily cycle and post-processing
The calculated UV quantities are corrected for the variation in the Earth–Sun
distance (see Sect. 3.1) and the attenuation caused by absorbing aerosols in
a post-processing step. After these corrections have been applied, the daily
doses and daily accumulated irradiances are calculated by integrating over
the 24 h time window centred at local solar noon. For this, a time
step of half an hour is used. It is worth emphasizing that the TROPOMI UV
algorithm does not account for variation in the cloud cover within the day,
but instead assumes that the cloud optical depth inferred from the overpass
measurement is valid for the whole day.
The absorbing aerosol correction follows the approach of
used in the OMI UV algorithm. It is based on a monthly aerosol climatology by
. The correction is a multiplicative factor
(Ca) which depends on the aerosol absorption optical depth
(τaa):
Ca=11+3τaa.
Here, the factor 3 in the denominator represents average conditions according
to earlier studies on the behaviour of satellite-estimated UV compared to
ground-based measurements and its dependence on τaa. found a significantly
reduced bias in the OMI UV product compared to ground-based measurements
over Europe after this correction had been applied.
The aerosol absorption optical depth depends on wavelength, but so does the
aerosol correction factor (Ca) that is applied in the TROPOMI UV
algorithm. Here, we utilize the aerosol optical depth and single scattering
albedo at 290, 315, 345, and 380 nm, available in the aerosol
climatology. These values are linearly interpolated to the wavelengths
included in the TROPOMI UV algorithm, after which the wavelength-specific
τaa is calculated. For the UV irradiances at selected
wavelengths (i.e. 305, 310, 324, and 380 nm), the TROPOMI UV
algorithm applies a wavelength-specific aerosol correction. For the
erythemally weighted and vitamin-D weighted UV irradiances, the aerosol
correction corresponding to 310 nm is applied.
The UV index as measured by a Brewer spectrophotometer in (a)
Jokioinen, and (b) Sodankylä on 13 August 2007 together with
results from the TROPOMI UV algorithm based on OMI measurements.
TROPOMI UV productOutput and example results
The TROPOMI L2 UV product includes the following UV quantities: the UV
irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV;
the vitamin-D weighted UV. Each of these are available as (i) a daily dose or
daily accumulated irradiance, (ii) overpass dose rate or irradiance, and
(iii) local noon dose rate or irradiance. In addition, all quantities are
available corresponding to actual cloud conditions and as clear-sky values,
corresponding to otherwise the same conditions but assuming a cloud-free
atmosphere. This makes 36 UV parameters altogether (see
Table ).
The L2 aerosol index and total ozone column products used as input to the UV
product are both based on measurements taken by TROPOMI's UVVIS spectrometer, band
3, which covers the wavelength range 320–405 nm.
The ground resolution of these measurements, and thus also of the TROPOMI UV
product, is 7×3.5km2 in nadir, while the largest pixels
throughout the swath are foreseen to be roughly 9×14km2.
The TROPOMI swath consists of 450 across-track pixels.
During the development of the TROPOMI UV algorithm, the UV processor software
has been tested using GOME-2 and OMI satellite data as a surrogate for real
TROPOMI measurements. The GOME-2 and OMI data have been processed using the
TROPOMI aerosol index and total ozone
algorithms to produce realistic TROPOMI-like L2 output.
Figure shows, as an example, the reflectance at
354 nm, the retrieved cloud optical depth, and the UV index of solar
noon produced using OMI-based test data for 13 August 2007, processed to
yield L2 aerosol index and total ozone output files that were given as input
to the TROPOMI UV algorithm. The Finnish UV measurement stations Jokioinen
(south-western Finland) and Sodankylä (northern Finland) are marked on
the map. The OMI overpass time for both stations was close to
10:30 UTC and less than 15 min from local solar noon.
The figure shows relatively high reflectances (R354) corresponding to
cloudy areas over the central Baltic (east of Sweden) as well as over large
parts of Sweden, Norway, Finland, and the Kola Peninsula. The cloud optical
depth in these areas varies from values below 5 to values over 50. Over the
western part of Russia, on the other hand, there is a rather cloud-free
region extending to the south-eastern part of Finland. In this area, cloud
optical depths are below 1.
The figure also shows the UV index (UVI) at local solar noon. The UVI has
been introduced by the World Health Organization as a tool
for informing the public about UV radiation. Thus, here we use the UVI to
demonstrate the example output of the TROPOMI UV algorithm. The UVI is
formulated based on the erythemally weighted UV dose rate, scaled to reach
a convenient number (i.e. the UVI is the erythemal dose rate in
Wm-2 multiplied by 40).
The solar noon UVI of Fig. reflects the aforementioned
variations in the cloud optical depth. Also, the noon solar zenith angle has
a strong influence on the UVI. UVI <2 prevails in the cloudy Scandinavian
and North Atlantic areas, while UVI >4 is present in the relatively
cloud-free areas of south-eastern Finland and western Russia. Further
south, cloud-free areas with UVI >8 can be seen south of the Black Sea,
and also in the mountainous regions between the Black Sea and the Caspian
Sea, where an influence of the altitude can be observed. South of the Black
Sea, in the immediate vicinity of the coast, there is a crescent-shaped area
showing UVI <4, with corresponding relatively high reflectivity and cloud
optical depth. Meteorological satellite products (Meteosat SEVIRI data
collected by the Finnish Meteorological Institute; not shown) confirm that
clouds are present over this area.
Figure shows a more detailed comparison of the TROPOMI UV
product with ground-based measurements taken by Brewer spectroradiometers
of the Finnish Meteorological Institute.
Table lists all 36 UV quantities of the L2 TROPOMI UV output
for the satellite pixel closest to Sodankylä.
The UVI measured by the Brewer spectrophotometer in Sodankylä
(Fig. ) shows reduced values due to clouds during the morning
and afternoon hours, while the values around noon are close to those expected
for cloud-free conditions. Also for Jokionen, the Brewer-measured UVI is
close to expected values for cloud-free conditions, although the midday hours
in general are somewhat cloudy. The very morning and late afternoon hours in
Jokioinen also appear cloud-free, with good agreement between the TROPOMI
clear-sky UVI and that measured by the Brewer. The retrieved effective cloud
optical depths are 2.3 and 3.0 for Sodankylä and
Jokioinen, indicating the presence of a cloud over both stations during the
satellite overpass. This is consistent with both the Brewer UV measurements
and with supporting satellite data (AVHRR data collected by the Finnish
Meteorological Institute; not shown). Finally, Fig. also
demonstrates the effect of assuming that the overpass cloud optical depth is
valid throughout the day: while the Brewer measurements indicate significant
variability in the UV irradiance caused by clouds, the TROPOMI UV (red curve)
is evenly attenuated throughout the day.
Expected uncertainty
The errors associated with the estimated UV quantities using the TROPOMI UV
algorithm are expected to be similar to the errors of the heritage
algorithms, namely the OMI surface UV product, which is most similar to that
of TROPOMI. For TROPOMI, no validation results are yet available, while OMI has been scrutinized in comparison to ground-based measurements in
a number of studies presented in the literature.
For OMI, summarized their validation results as follows:
For flat, snow-free regions with modest loadings of absorbing aerosols or
trace gases, the OMI-derived daily erythemal doses have a median
overestimation of 0–10 %, and some 60 to 80 % of the doses
are within ±20% from the ground reference. For sites
significantly affected by absorbing aerosols or trace gases one expects, and
observes, bigger positive bias up to 50 %. For high-latitude sites
the satellite-derived doses are occasionally up to 50 % too small
because of unrealistically small climatological surface albedo.
After inclusion of the absorbing aerosol correction in the OMI algorithm, it
is expected that the overestimation due to aerosols should have reduced
considerably, which indeed was the case for the European stations included in
the study of . However, even after this correction, a
systematic overestimation of 20–30 % remained for Rome (Italy) and
Reading (England). Furthermore, it is worth noting that the aerosol
climatology represents typical or average conditions, which means that day-to-day
variations in the aerosol load at polluted locations may still cause
occasional strong overestimation in the surface UV.
A recent study by assessed errors in the OMI UV over
high latitudes, caused by inaccuracies in the surface UV albedo climatology
used in the algorithm. Their results show that the OMI UV can have a bias
exceeding 50 % – in both negative and positive directions – when
the OMI surface albedo is too high or too low. Note, however, that, although
the percentage error may seem large, the figures of
correspond to conditions with relatively low sun and therefore the errors
remain small on an absolute scale.
A more comprehensive uncertainty analysis of the TROPOMI UV product is
planned, which will be based on uncertainties in the inputs given to the
LUTs and how the uncertainties of all input parameters combined influence
the estimated surface UV.
Conclusions
This paper describes the TROPOMI UV algorithm. The algorithm has been tested
using realistic input, based on OMI and GOME-2 satellite measurements. These
preliminary results indicate that the algorithm is functioning according to
expectations, also when compared with ground-based Brewer spectrophotometer
UV measurements in Finland. A proper evaluation of the performance of the
TROPOMI UV product can, however, only be done after the launch, when real data
start becoming available.
There is a strong need for continued monitoring of the UV radiation reaching
the Earth's surface. The TROPOMI UV record will build upon the heritage of
satellite-retrieved surface UV that starts with TOMS in 1978 and continues
to the present thanks to the OMI UV record see,
e.g..
Data availability
The Brewer UV data are available through the European UV
database, EUVDB, http://uv.fmi.fi/uvdb/ (Heikkilä et al., 2016). The satellite data used are
available from the corresponding author on request.
Author contributions
AVL designed the presented algorithm with help from all
co-authors. AVL, JK, and NK implemented the algorithm with help from NAK, MS,
AA and JT. AH, KL and TM helped to interpret the results. All co-authors participated in writing the manuscript.
Competing interests
The authors declare that they have no conflict of
interest.
Special issue statement
This article is part of the special issue on “TROPOMI on
Sentinel-5 Precursor: data products and algorithms”. It is not associated
with a conference. Edited by: Jhoon Kim
Reviewed by: two anonymous referees
References
Aphalo, P., Albert, A., Björn, L., Ylianttila, L., Figueroa, F. L., and
Huovinen, P.: Beyond the Visible: A Handbook of Best Practice in Plant UV
Photobiology, Chap. 1 Introduction, 21–27, COST Action FA0906
UV4growth. University of Helsinki, Department of Biosciences, Division of
Plant Biology, Helsinki, 2012.Arola, A., Kazadzis, S., Krotkov, N., Bais, A., Gröbner, J., and Herman, J. R.: Assessment of TOMS UV bias due to absorbing aerosols, J. Geophys. Res., 110, D23211, 10.1029/2005JD005913, 2005.Arola, A., Kazadzis, S., Lindfors, A., Krotkov, N., Kujanpää, J.,
Tamminen, J., Bais, A., di Sarra, A., Villaplana, J. M., Brogniez, C.,
Siani, A. M., Janouch, M., Weihs, P., Webb, A., Koskela, T., Kouremeti, N.,
Meloni, D., Buchard, V., Auriol, F., Ialongo, I., Staneck, M., Simic, S.,
Smedley, A., and Kinne, S.: A new approach to correct for absorbing aerosols
in OMI UV, Geophys. Res. Lett., 36, L22805, 10.1029/2009GL041137, 2009.Bernhard, G., Arola, A., Dahlback, A., Fioletov, V., Heikkilä, A., Johnsen, B., Koskela, T., Lakkala, K., Svendby, T., and Tamminen, J.: Comparison of OMI UV observations with ground-based measurements at high northern latitudes, Atmos. Chem. Phys., 15, 7391–7412, 10.5194/acp-15-7391-2015, 2015.
Blumthaler, M. and Ambach, W.: Solar UVB-albedo of various surfaces, Photochem. Photobiol., 48, 85–88, 1988.Bugliaro, L., Mayer, B., Meerkötter, R., and Verdebout, J.: Potential and limitations of space-based methods for retrieval of
surface UV-B daily doses: a numerical study, J. Geophys. Res., 111, D23207, 10.1029/2005JD006534, 2006.Calbo, J., Pages, D., and Gonzalez, J.-A.: Empirical studies of cloud effects on UV radiation: a review,
Rev. Geophys., 43, 1–28, 10.1029/2004RG000155, 2005.
CIE: Action spectrum for the production of previtamin D3 in human skin, Tech. Rep. 174, Commission Internationale de l'Eclairage (International Commission on Illumination), Vienna, Austria, 2006.
Ciren, P. and Li, Z.: Long-term global Earth surface ultraviolet radiation exposure derived from ISCCP and TOMS satellite measurements, Agr. Forest Meteorol., 120, 51–68, 2003.
Danielson, J. J. and Gesch, D. B.: Global multi-resolution terrain elevation data 2010 (GMTED2010),
Tech. Rep. 2011–1073, U.S. Geological Survey, Reston, Virginia, 2011.
Degünther, M. and Meerkötter, R.: Influence of inhomogeneous surface albedo on UV irradiance: effect of a stratus cloud, J. Geophys. Res., 105, 22755–22761, 2000.
Degünther, M., Meerkötter, R., Albold, A., and Seckmeyer, G.: Case study on the influence of inhomogeneous surface albedo on UV irradiance, Geophys. Res. Lett., 25, 3587–3590, 1998.
Deirmendjian, D.: Electromagnetic Scattering on Spherical Polydispersions, American Elsevier Publishing Company Inc., New York, 1969.den Outer, P. N., Slaper, H., and Tax, R. B.: UV radiation in the Netherlands: assessing long-term variability and trends in relation to ozone and clouds, J. Geophys. Res., 110, D02203, 10.1029/2004JD004824, 2005.Dobber, M., Voors, R., Dirksen, R., Kleipool, Q., and Levelt, P.: The high-resolution solar reference spectrum between 250 and 550 nm and its application to measurements with the ozone monitoring instrument, Sol. Phys., 249, 281–291, 10.1007/s11207-008-9187-7, 2008.
Eck, T. F., Bhartia, P. K., and Kerr, J. B.: Satellite estimation of spectral UVB irradiance using TOMS derived total ozone and UV reflectivity, Geophys. Res. Lett., 22, 611–614, 1995.Farman, J. C., Gardiner, B. G., and Shanklin, J. D.: Large losses of total ozone in Antarctica reveal seasonal ClOx/NOx interaction, Nature, 315, 207–210, 1985.
Feister, U. and Grewe, R.: Spectral albedo measurements in the UV and visible region over different types of surfaces, Photochem. Photobiol., 62, 736–744, 1995.Gadhavi, H., Pinker, R. T., and Laszlo, I.: Estimates of surface ultraviolet radiation over north America using geostationary operational environmental satellites observations,
J. Geophys. Res., 113, D21205, 10.1029/2007JD009308, 2008.
Gröbner, J., Albold, A., Blumthaler, M., Cabot, T., De la Casiniere, A., Lenoble, J., Martin, T., Masserot, D., Muoeller, M., Philipona, R., Pichler, T., Pougatch, E., Rengarajan, G., Schmucki, D., Seckmeyer, G., Sergent, C., Toureo, M., and Weihs, P.: Variability of spectral solar ultraviolet irradiance in an Alpine environment, J. Geophys Res., 105, 26991–27003, 2000.Gröbner, J., Schreder, J., Kazadzis, S., Bais, A. F., Blumthaler, M., Görts, P., Tax, R., Koskela, T., Seckmeyer, G., Webb, A. R., and Rembges, D.: Traveling reference spectroradiometer for routine quality assurance of spectral solar ultraviolet irradiance measurements, Appl. Optics, 44, 5321–5331, 10.1364/AO.44.005321, 2005.Heikkilä, A., Kaurola, J., Lakkala, K., Karhu, J. M., Kyrö, E., Koskela,
T., Engelsen, O., Slaper, H., and Seckmeyer, G.: European UV DataBase (EUVDB)
as a repository and quality analyser for solar spectral UV irradiance
monitored in Sodankylä, Geosci. Instrum. Method. Data Syst., 5, 333–345,
10.5194/gi-5-333-2016, 2016 (data available at:
http://uv.fmi.fi/uvdb/, last access: 12 February 2018).
Herman, J. R. and Celarier, E. A.: Earth surface reflectivity climatology at 340 nm to 380 nm from TOMS data, J. Geophys. Res., 102, 28003–28011, 1997.Herman, J. R., Labow, G., Hsu, N. C., and Larko, D.: Changes in cloud and aerosol cover (1980–2006) from reflectivity time series using SeaWiFS, N7-TOMS, EP-TOMS, SBUV-2, and OMI
radiance data, J. Geophys. Res.-Atmos., 114, D01201, 10.1029/2007JD009508, 2009.Ialongo, I., Arola, A., Kujanpää, J., and Tamminen, J.: Use of satellite erythemal UV products in analysing the global UV changes, Atmos. Chem. Phys., 11, 9649–9658, 10.5194/acp-11-9649-2011, 2011.
Josefsson, W. and Landelius, T.: Effect of clouds on UV irradiance: as estimated from cloud amount, cloud type, precipitation, global radiation and sunshine duration, J. Geophys. Res., 105, 4927–4935, 2000.Kinne, S., O'Donnel, D., Stier, P., Kloster, S., Zhang, K., Schmidt, H., Rast, S., Giorgetta, M., Eck, T. F., and Stevens, B.: MAC-v1: a new global aerosol climatology for climate studies, J. Adv. Model. Earth Sy., 5, 704–740, 10.1002/jame.20035, 2013.
Krotkov, N. A., Bhartia, P. K., Herman, J. R., Fioletov, V., and Kerr, J. B.: Satellite estimation of spectral surface UV irradiance in the presence of tropospheric aerosols 1: cloud-free case, J. Geophys. Res., 103, 8779–8793, 1998.
Krotkov, N. A., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Fioletov, V.: Satellite estimation of spectral surface UV irradiance 2: effect of horizontally homogeneous clouds and snow, J. Geophys. Res., 106, 11743–11759, 2001.Krotkov, N., Bhartia, P. K., Herman, J., Slusser, J., Scott, G., Labow, G.,
Vasilkov, A. P., Eck, T. F., and Holben, B.: Aerosol ultraviolet absorption
experiment (2002 to 2004) – Part 2: absorption optical thickness, refractive
index, and single scattering albedo, Opt. Eng., 44, 041005,
10.1117/1.1886819, 2005.Kujanpää, J. and Kalakoski, N.: Operational surface UV radiation product from GOME-2 and AVHRR/3 data, Atmos.
Meas. Tech., 8, 4399–4414, 10.5194/amt-8-4399-2015, 2015.
Kylling, A., Bais, A. F., Blumthaler, M., Schreder, J., Zerefos, C. S., and Kosmidis, E.: Effect of aerosols on solar UV irradiances during photochemical activity and solar ultraviolet radiation campaign, J. Geophys. Res., 103, 26051–26060, 1998.Lakkala, K., Arola, A., Heikkilä, A., Kaurola, J., Koskela, T., Kyrö, E., Lindfors, A., Meinander, O., Tanskanen, A., Gröbner, J., and Hülsen, G.: Quality assurance of the Brewer spectral UV measurements in Finland, Atmos. Chem. Phys., 8, 3369–3383, doi.org/10.5194/acp-8-3369-2008, 2008.
Lenoble, J.: Modeling of influence of snow reflectance on ultraviolet irradiance for cloudless sky, Appl. Optics, 37, 2441–2447, 1998.Lindfors, A. and Arola, A.: On the wavelength-dependent attenuation of UV radiation by clouds, Geophys. Res. Lett., 35, L05806, 10.1029/2007GL032571, 2008.Lindfors, A., Kaurola, J., Arola, A., Koskela, T., Lakkala, K., Josefsson, W., Olseth, J. A., and Johnsen, B.: A method for reconstruction of past UV radiation based on radiative transfer modeling: applied to four stations in northern Europe, J. Geophys. Res., 112, D23201, 10.1029/2007JD008454, 2007.Lindfors, A., Tanskanen, A., Arola, A., van der A, R., Bais, A., Feister, U., Janouch, M., Josefsson, W., Koskela, T., Lakkala, K., den Outer, P. N., Smedley, A. R. D., Slaper, H., and Webb, A. R.: The PROMOTE UV record: toward a global satellite-based climatology of surface ultraviolet irradiance, IEEE J. Sel. Top. Appl., 2, 207–212, 10.1109/JSTARS.2009.2030876, 2009.
Loots, E., Babic, L., Kissi-Ameyaw, J., Smeets, J., Braak, R., Kleipool, Q., Ludewig, A., Vacanti, G.,
Dierssen, W., Leloux, J., and Rozemeijer, N.: Algorithm theoretical basis document for the
TROPOMI L01b data processor, Tech. rep., Royal Netherlands Meteorological Institute, De Bilt, 2016.
Lubin, D. and Frederick, J. E.: The ultraviolet radiation environment of the Antarctic peninsula: the roles of ozone and cloud cover, J. Appl. Meteorol., 30, 478–493, 1991.
Matthijsen, J., Slaper, H., Reinen, A. G. M., and Velders, G. J. M.: Reduction of solar UV by clouds: a remote sensing approach compared with ground based measurements, J. Geophys. Res., 105, 5069–5080, 2000.Spurr, R. J.: VLIDORT: a linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media, J. Quant. Spectrosc. Ra., 102, 316–342, 10.1016/j.jqsrt.2006.05.005, 2006.Spurr, R., Loyola, D., Roozendael, M. V., and Lerot, C.: S5P/TROPOMI Total Ozone ATBD,
available at: http://www.tropomi.eu/data-products/level-2-products (last access: 5 February 2018),
issue 1.0, 2016.Stein Zweers, D.: TROPOMI ATBD of the UV aerosol index, available at:
http://www.tropomi.eu/data-products/level-2-products (last access: 5 February 2018),
issue 1.0, 2016.
Tanskanen, A.: Lambertian surface albedo climatology at 360 nm from TOMS data using moving time-window technique,
in: OZONE, Proceedings XX Quadrennial Ozone Symposium, 1–8 June 2004, vol. II, 1159–1160, Athens, Greece, 2004.
Tanskanen, A., Krotkov, N., Herman, J. R., and Arola, A.: Surface ultraviolet irradiance from OMI, IEEE T. Geosci. Remote, 44, 1267–1271, 2006.Tanskanen, A., Lindfors, A., Määttä, A., Krotkov, N., Herman, J., Kaurola, J., Koskela, T., Lakkala, K., Fioletov, V., Bernhard, G., McKenzie, R., Kondo, Y., O'Neill, M., Slaper, H., den Outer, P., Bais, A. F., and Tamminen, J.: Validation of daily erythemal doses from ozone monitoring instrument with
ground-based UV measurement data, J. Geophys. Res., 112, D24S44, 10.1029/2007JD008830, 2007.Thalman, R. and Volkamer, R.: Temperature dependent absorption cross-sections of O2-O2 collision pairs between 340 and 630 nm and at atmospherically relevant pressure, Phys. Chem. Chem. Phys., 15, 15371–15381, 10.1039/C3CP50968K, 2013.UN: Montreal Protocol on Substances that Deplete the Ozone Layer, United
Nations – Treaty Series, 1522, United Nations, New York, available at:
https://treaties.un.org/doc/Publication/UNTS/Volume 1522/v1522.pdf
(last access: 5 February 2018),
1989.
UNEP: Environmental effects of ozone depletion and its interactions with climate change: 2010 assessment, Photoch. Photobio. Sci., 10, 165–320, 2011.
UNEP: Environmental effects of ozone depletion and its interactions with climate change: 2014 assessment, Photoch. Photobio. Sci., 14, 1–186, 2015.
Verdebout, J.: A method to generate surface UV radiation maps over Europe using GOME, Meteosat, and ancillary geophysical data, J. Geophys. Res., 105, 5049–5058, 2000.
Weatherhead, B., Tanskanen, A., Stevermer, A., Andersen, S., Arola, A.,
Austin, J., Bernhard, G., Browman, H., Fioletov, V., Grewe, V., Herman, J.,
Josefsson, W., Kylling, A., Kyrö, E., Lindfors, A., Shindell, D.,
Taalas, P., and Tarasick, D.: ACIA 2005, Chap. 5: Ozone and Ultraviolet
Radiation, 151–182, Cambridge University Press, New York, 2005.Webb, A. R., Slaper, H., Koepke, P., and Schmalwieser, A. W.: Know your standard: clarifying the CIE erythema action spectrum, Photochem. Photobiol., 87, 483–486, 10.1111/j.1751-1097.2010.00871.x, 2011.Wellemeyer, C., Taylor, S., Seftor, C., McPeters, R., and Bhartia, P.: A correction for total ozone mapping spectrometer profile shape errors at high latitude, J. Geophys. Res.-Atmos., 102, 9029–9038, 10.1029/96JD03965, 1997.WHO: Global Solar UV Index: A Practical Guide, World Health Organization,
available at: http://www.who.int/uv/publications/globalindex/en/ (last access: 5 February 2018), 2002.Williamson, C. E., Zepp, R. G., Lucas, R. M., Madronich, S., Austin, A. T., Ballare, C. L., Norval, M., Sulzberger, B., Bais, A. F., McKenzie, R. L., Robinson, S. A., Haeder, D.-P., Paul, N. D., and Bornman, J. F.: Solar ultraviolet radiation in a changing climate, Nat. Clim. Change, 4, 434–441, 10.1038/NCLIMATE2225, 2014.
WMO: Scientific assessment of Stratospheric Ozone: 1989, World Meteorological
Organization (WMO), Global Ozone Research and Monitoring Project–Report No.
20, United Nations Environment Program, Nairobi, Kenya, 1989.Zempila, M.-M., van Geffen, J. H. G. M., Taylor, M., Fountoulakis, I., Koukouli, M.-E., van Weele, M., van der A, R. J., Bais, A., Meleti, C., and Balis, D.: TEMIS UV product validation using NILU-UV ground-based measurements in Thessaloniki, Greece, Atmos. Chem. Phys., 17, 7157–7174, 10.5194/acp-17-7157-2017, 2017.