AMTAtmospheric Measurement TechniquesAMTAtmos. Meas. Tech.1867-8548Copernicus GmbHGöttingen, Germany10.5194/amt-8-4369-2015Relative drifts and biases between six ozone limb satellite measurements from the last decadeRahpoeN.nabiz@iup.physik.uni-bremen.dehttps://orcid.org/0000-0002-6654-8293WeberM.https://orcid.org/0000-0001-8217-5450RozanovA. V.WeigelK.https://orcid.org/0000-0001-6133-7801BovensmannH.BurrowsJ. P.https://orcid.org/0000-0003-1547-8130LaengA.StillerG.https://orcid.org/0000-0003-2883-6873von ClarmannT.KyröläE.https://orcid.org/0000-0001-9197-9549SofievaV. F.https://orcid.org/0000-0002-9192-2208TamminenJ.https://orcid.org/0000-0003-3095-0069WalkerK.https://orcid.org/0000-0003-3420-9454DegensteinD.BourassaA. E.HargreavesR.BernathP.UrbanJ.https://orcid.org/0000-0001-7026-793XMurtaghD. P.https://orcid.org/0000-0003-1539-3559Institute of Environmental Physics,
University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, GermanyKarlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Karlsruhe, GermanyFinnish Meteorological Institute, Helsinki, FinlandDepartment of Physics, University of Toronto, Toronto, CanadaInstitute for Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaDepartment of Chemistry, University of York, York, UKChalmers University of Technology, Department of Earth and Space Sciences, 41296 Gothenburg, SwedenDepartment of Chemistry & Biochemistry, Old Dominion University, Norfolk, VA, USAN. Rahpoe (nabiz@iup.physik.uni-bremen.de)16October20158104369438116February201510April201529September201530September2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://amt.copernicus.org/articles/8/4369/2015/amt-8-4369-2015.htmlThe full text article is available as a PDF file from https://amt.copernicus.org/articles/8/4369/2015/amt-8-4369-2015.pdf
As part of European Space Agency's (ESA) climate change initiative, high vertical resolution ozone
profiles from three instruments all aboard ESA's Envisat (GOMOS, MIPAS,
SCIAMACHY) and ESA's third party missions (OSIRIS, SMR,
ACE-FTS) are to be combined in order to create an essential climate variable
data record for the last decade. A prerequisite before combining data is the
examination of differences and drifts between the data sets. In this paper, we
present a detailed analysis of ozone profile differences based on pairwise
collocated measurements, including the evolution of the differences with
time. Such a diagnosis is helpful to identify strengths and weaknesses of
each data set that may vary in time and introduce uncertainties in long-term
trend estimates. The analysis reveals that the relative drift between the
sensors is not statistically significant for most pairs of instruments. The
relative drift values can be used to estimate the added uncertainty in
physical trends. The added drift uncertainty is estimated at about
3 % decade-1 (1σ). Larger differences and variability in
the differences are found in the lowermost stratosphere (below 20 km) and in
the mesosphere.
Introduction
Ozone as the main absorber in the UV
wavelength region is one of the crucial atmospheric trace gases which has
been investigated extensively in the past 40 years due to its role as
a protecting shield against UV radiation that is harmful for living species.
Different observation techniques have been used to extract the ozone signal
from the troposphere to the mesosphere .
Due to a limited lifetime of a single space instrument, long-term studies on
ozone require a combination of measurements from different instruments to be
merged to obtain a coherent climate data record. For this purpose the merging
of the data sets from several instruments is one possible method. In order to
have the best observations included in the merged data, information about
biases and drifts is needed for the optimal use of the data. Similar
activities on merging are performed by GOZCARDS (Global OZone Chemistry And
Related trace gas Data records for the Stratosphere) for SAGE I, SAGE II,
ACE-FTS, and MLS-Aura and by a combination of
SAGE II and GOMOS and SAGE II and OSIRIS
. This paper deals with the intercomparison of six
limb ozone data sets in the framework of the ESA (European Space Agency)
climate change initiative (O3 CCI) and is part of the ongoing merging
activities
(See SI2N special issue and papers therein for an overview).
Trend estimation of stratospheric ozone of sensors used in this paper have
been evaluated by SCIAMACHY , MIPAS
, GOMOS , and OSIRIS
(see Sect. 5.2). Each instrument
of the CCI data sets has been validated by comparison with correlative
measurements to establish the uncertainty and precision
.
One important aspect of this work is that the intercomparisons are carried out for
each possible sensor pair. A linear regression model has been applied in order to determine the differences
and drifts between all pairs of instruments. The differences and drifts can be used to estimate drift-corrected trends of
the merged pairs and overall merged product.
The paper is divided into five sections. In Sect. 2 we describe briefly the
instruments and their performance. In Sect. 3 basic formulae and definitions
for the pairwise comparisons are summarized. In Sect. 4, an overview of the
time series from the intercomparisons with SCIAMACHY is provided. In Sect. 5
results from the regression model for the combination of all sensors are
discussed and compared with other similar intercomparison and validation
works and a summary of the main results and concluding remarks are given.
Instruments
The six instruments used for the comparison in this work are carried by three
different satellites. Three atmospheric chemistry experiments (GOMOS, MIPAS,
and SCIAMACHY) were onboard the Envisat satellite, which operated from 2002 to 2012.
It flew in a sun-synchronous orbit at an altitude of 780 km, leading to
an orbital period of ≈ 100 min and 14 orbits per day. OSIRIS and
SMR aboard Odin are two instruments which have been taking measurements since 2001 and are
still operating. Odin circles the Earth in a polar, sun-synchronous,
near-terminator orbit with an inclination of 97.8∘ at an altitude of
600 km. ACE-FTS has been providing measurements since 2004 on SCISAT that has a
circular orbit with an inclination of 74∘ at an altitude of
650 km.
All instruments are briefly described in the following subsections.
Table gives an overview of the time period used
for the intercomparison, local time of the measurements, vertical resolution,
precision and other instrument-specific information. More details on the
instruments, their performance, and validation can be found in
.
GOMOS on Envisat
GOMOS (Global Ozone Monitoring by Occultation of Stars) is the stellar
occultation instrument onboard the Envisat satellite that exploits the
absorption and scattering of stellar light in ultraviolet (UV), visible and
near-infrared wavelengths to retrieve vertical profiles of ozone,
NO2, NO3, O2, H2O, and aerosol extinction
. Ozone number density profiles are
retrieved from measurements by the UV-Vis spectrometer in the altitude range
≈10–100 km. The vertical resolution
of GOMOS ozone profiles is 2 km below 30 and 3 km above
40 km with the linear transition between. The estimated uncertainty
of the retrieved ozone profiles is 0.5–5 %. In this paper GOMOS ozone profiles processed with
IPF 6.0 are used.
MIPAS on Envisat
MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) aboard
Envisat is a middle infrared Fourier transform spectrometer measuring
atmospheric emission spectra in limb mode . MIPAS
measurements include CH4, H2O, HNO3, N2O,
NO2, HNO3, HNO4, N2O5, PAN, CH4,
C2H2, C2H6, CO, H2CO, HCN, HCOOH, ClO,
ClONO2, HOCl CFC-11, CFC-12, HCFC-22, and SO2, as well as NO, HNO3, HNO4, N2O5, PAN,
C2H2, C2H6, CO, HCN, HCOOH,
ClO, ClONO2, HOCl, CFC-11, CFC-12, HCFC-22,
SO2, O3, temperature, and pressure profiles. The high-resolution measurements (0.025 cm-1) are performed from 685 to
2410 cm-1 (14.6 to 4.15 µm) for the years 2002–2004.
The vertical resolution ranges from 3 to 8 km in the altitude range
from 6 to 68 km. After an anomaly in the interferometric drive, the
operational mode has been switched to lower spectral resolution with a finer
vertical grid . In this work we use data from
2005 onwards, which is the low-resolution mode that is currently available
from MIPAS-IMK version R 220 .
Overview of data sets used (adopted from ).
If necessary, the profiles were converted to volume mixing ratio (vmr) and interpolated to a
1 km vertical grid.
InstrumentsTime periodLocal timeVertical resolutionEstimatedAverage numberOriginal ozone unitSource ofprecisionof profiles/dayand Level 2 gridtemperatureSCIAMACHY2002–201210:00profile-dependent,10–15 % 1300number densityECMWF3–5 kmfixed altitude gridanalysisGOMOS2002–201222:002 km below 30 km,0.5–5 % 110number densityECMWF3 km above 40 km,tangent altitude gridanalysisa linear transition between 30 and 40 kmOSIRIS2002–201206:002 km–3 km,2–10 % 250number densityECMWF18:00altitude-dependentfixed altitude gridanalysisMIPAS2005–201210:00profile-dependent,1–4 % 1000vmr on fixedRetrieved22:003–5 kmaltitude gridACE-FTS2004–2010sunrise3 km1–3 % 11vmr on fixedRetrievedsunsetaltitude gridSMR2002–201206:00profile-dependent,20 % 250vmr on fixedECMWF18:002.5–3.5 kmaltitude gridanalysisSCIAMACHY on Envisat
SCIAMACHY measures the Earth's atmosphere in three observation modes, i.e.
nadir, limb and occultation
. In limb mode, SCIAMACHY
scans the atmosphere in 3.3 km steps vertically and 960 km
across-track. SCIAMACHY covers the wavelengths between 212 and
2386 nm, divided into eight channels. Atmospheric trace gases such as
BrO, CH4, CO, CO2, H2O, IO,
NO2, OClO, O2, O3, NO2, SO2,
and aerosol extinction can be retrieved with SCIAMACHY
.
The retrieved SCIAMACHY ozone profiles from the version V2.5 are used in this study
The algorithm, validation, and error analysis are described in
, , and , respectively.
OSIRIS on Odin
OSIRIS (Optical Spectrograph and InfraRed Imager System) is the instrument
onboard the Odin satellite that was launched on 20 February 2001
. OSIRIS measures the ozone
number density profiles with a vertical resolution of 1–3 km in
a limb mode from 10 to 70 km. The measurement is performed in the
optical spectral range of 280–800 nm with a resolution of
1 nm. In this work the OSIRIS ozone data V5.01 have been used
.
SMR on Odin
The second instrument on the Odin satellite is SMR (Sub-millimeter and
Millimeter Radiometer) which uses heterodyne radiometers to measure thermal
emission in the frequency range of 486–581 GHz. Atmospheric species
measured in the frequency bands at 501.8 and 544.6 GHz are
ClO, HNO3, N2O, and O3. For this study we use the SMR ozone data version 2.1
processed at the Chalmers University of Technology, Gothenburg, Sweden. The
optimal estimation method (OEM) scheme is used to retrieve the ozone VMR from
the O3 line at 501.8 GHz.
ACE-FTS on SCISAT
The solar occultation instrument ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) onboard the Canadian satellite mission SCISAT
was launched on 12 August 2003 . It measures
high-resolution (0.02 cm-1) spectra between 750 and
4400 cm-1 (2.2–13 µm). The vertical resolution of the
profiles is 3–4 km with a sampling of 1.5–6 km. More than
30 trace gases, temperature, and pressure are retrieved by ACE-FTS using
a modified global fit approach based on the Levenberg–Marquardt non-linear
least-squares method . In this study we use the
ACE-FTS ozone profiles version 3.0 retrieved at the University of Waterloo
.
Methodology and definitions
Ozone volume mixing ratios on a common fixed
altitude grid with 1 km spacing are used in this study. All profiles have been converted,
regridded, and interpolated, if necessary, from native ozone profiles using pressure and temperature either from
meteorological analyses or retrieved using
the same instrument (see Table ).
The screening and filtering of the data sets was performed as follows:
SCIAMACHY: only cloud-free profiles are used;
GOMOS: no screening is performed by us;
OSIRIS: outliers are screened out for negative ozone values and ozone volume mixing ratio
(vmr) > 15 ppmv;
MIPAS: screening for zero visualization values (VizO3=0) and diagonal elements of
averaging kernels AKdiag< 0.03, as recommended by the data
providers;
ACE-FTS: if ozone values were negative and errors were larger than 100 %, as recommended by the data
providers;
SMR: for poor-quality data sets with the flag set to zero, e.g. quality =0, as recommended by the data providers.
In our analyses, we use collocated measurements for each pair of instruments.
The collocation criteria depend on the sampling and coverage of the satellite
pair in such a way that a sufficient number of profile pairs is achieved. Specific
collocation criteria and the total number of collocations are listed in
Tables and ,
respectively. The sensitivity on collocation criteria have been performed for
5 and 12 h in the case of MIPAS and OSIRIS. No major differences have
been observed for the variation of collocation criteria in stratosphere for
this case
The relative difference (δ) is calculated for collocated single
profile pairs in a given month, altitude, and latitude bins (5, 15, and
30∘) as follows:
δi(z)=2⋅xci-xriXc+Xr.
The mean relative
difference (Δ) is the monthly mean of the δ's at altitude z as follows:
Δ(z)=∑iδi(z)N(z),
where xci and xri correspond to the collocated
single ozone profiles of the comparison instrument (c) and the “reference”
instrument (r) with Xc and Xr as monthly mean
averages of xci and xri, respectively.
N(z) is the number of available pairs at altitude z for a
given month and latitude bin. The standard deviation of Δ is
calculated as follows:
σ(z)=∑i=1N(z)[δi(z)-Δ(z)]2N(z)-1.
In addition to the relative difference we also applied a linear regression to the monthly
mean relative difference time series for each altitude and latitude bin.
The mean relative difference between two instruments
is not necessarily a constant but can vary with time.
We analyse this time dependence by using a multilinear regression model:
Δ(t,z)=α(z)⋅(t-t∗)+β(z)+∑i2[κi(z)sin(ωit)+νi(z)cos(ωit)]+R(t,z),
where Δ(t,z) is the monthly mean relative difference time series for
each altitude and latitude bin. The slope α(z) is the “pairwise
relative drift” and β(z) is the “pairwise relative bias” derived
from the regression function.
The term “bias” is avoided here, since the comparison is not based on one
reference sensor but rather each sensor is used as a reference. Instead of
“bias” the terms “pairwise relative bias” and “pairwise relative drift”
between two instruments are more appropriate here and refer hereafter to
“relative bias” and “relative drift” denoted by the Greek symbols
β(z) and α(z), respectively. Non-linearity effects are not
accounted for here.
The corresponding α(z), β(z) are derived using a
multivariate linear regression and the autocorrelation method. The noise term
R(t,z) is assumed to be autoregressive function with lag one AR(1). We used
the methods described in and to
derive autocorrelation, white noise, σα, and σβ,
respectively, for each pair of instruments. Only time series with number of
months larger than 36 are used for the analysis. For the periodic variation,
periods of 6 and 12 months have been considered with corresponding harmonic
functions and parameters κ(z), ν(z). No proxies of the
quasi-biennial oscillation or other natural variability have been considered
because natural effects are assumed to cancel out when differences are
calculated. Since MIPAS RR (reduced resolution) profiles are only available
from January 2005 onwards, February 2005 was used as reference time
t∗ or in other words, the relative bias β(z) is the observed
bias at time t∗.
Relative difference time series
In this part, only a brief example of mean relative difference time series is
presented with SCIAMACHY as the reference instrument.
In Sect. 5 the results from the regression analyses (relative bias and
relative drifts) of all sensors as reference instrument are discussed. We
could have chosen any instrument as we consider none of the instruments as an
absolute reference. SCIAMACHY is the only data set under investigation from
a dense sampler covering the full Envisat observation period. Further details
from all possible pair combinations from 5∘ latitude bin analyses can
be viewed as contour plots for β(z) and α(z) as Supplement.
The monthly mean relative difference time series of all CCI limb data with
respect to SCIAMACHY for different latitude bands are presented in
Figs. –.
In the Arctic (70–60∘ N, Fig. ) most of the data sets agree to
within ±10% for all altitudes between 25 and
40 km with SCIAMACHY. The best agreement for most instruments with SCIAMACHY is found at 25 km. Above 30 km, MIPAS showed a pronounced
seasonal cycle compared to SCIAMACHY. SCIAMACHY tends to be lower than the other instruments at 30 km.
At northern mid-latitudes (50–40∘ N, Fig. )
the best agreement with SCIAMACHY is at 30 km and below. At 30 km and above, SCIAMACHY is lower than
ACE-FTS and MIPAS; at 40 km, SCIAMACHY is in agreement with MIPAS, but
higher than the other data sets by up to 10 %.
Collocation criteria in time (hours) and distance (km).
Mean relative
difference Δ(z) time series between all instruments (comparison sensor) and SCIAMACHY (reference sensor) in the
latitude band 70–60∘ N.
Same as Fig. , but for the northern middle latitudes
(50–40∘ N).
Same as Fig. , but for the tropical latitudes
(10–0∘ N).
In the tropics (0–10∘ N, Fig. ), at
25 km, SCIAMACHY is lower than most of the other instruments, but all
instruments agree to within ±5 % with SCIAMACHY. It is apparent
that SMR data are quite noisy at this altitude. At 30 km, agreement is
similar, except that SCIAMACHY shows a consistent positive bias of about
+10 %. At 35 km, SMR shows a negative bias of about -5 to
-10 % with respect to SCIAMACHY and is quite noisy. At
40 km, MIPAS and SCIAMACHY are in very good agreement. SCIAMACHY is
10 % higher on average than all other data at this altitude, similar
to what is observed at northern mid-latitudes
(Fig. ).
From these figures it is evident that the difference time series are smoothest for a pair of
dense samplers like MIPAS and SCIAMACHY. Part of the variability seen in the difference time series,
thus, are a consequence of the different sampling statistics.
Intercomparison results and discussion
In order to get an overall picture of the pairwise comparisons with each
instrument as a reference sensor, the vertical distribution of β
(relative bias) is drawn in Fig. for
30∘ S–30∘ N at altitudes between 20 km and
50 km in 5 km steps. Each colour identifies the reference
sensor. The position of the different symbols mark the value of each
comparison sensor relative to the reference sensor. This compact
representation gives a detailed view of the performance of each sensor.
(a) “Pairwise relative bias” (β) range for all sensors as a function of
altitude in the tropical band (30∘ S–30∘ N). Reference sensors are indicated by colour and individual comparison sensors by corresponding symbols.
(b) Same as (a) but only significant β values are shown (non-significant values are shaded out).
Same as Fig. but for the northern middle
latitudes (30–60∘ N).
Same as Fig. but for the southern middle
latitudes (30–60∘ S).
(a) Relative drift (α) range for all sensors as a function of altitude in the tropical
band (30∘ S–30∘ N). Reference
sensors are indicated by colour and individual comparison sensors by corresponding symbols.
(b) Same as (a) but only significant α values are shown (non-significant values are shaded out).
Same as Fig. but for the northern middle latitudes (30–60∘ N).
Same as Fig. but for the southern middle latitudes (30–60∘ S).
In the lowermost stratosphere (LS) the β range is large for most of the
instruments. The smallest β range for most of the reference sensors is
observed at 25 km which is to within ±5%. Only MIPAS
and GOMOS have a slightly larger absolute β with respect to SMR. At
30 km, the β range is within ±5% except for SCIAMACHY
as the reference sensor, showing a positive β with respect to four
comparison sensors.
Between 35 and 50 km, the β range increases for each sensor and
shows different behaviour. Four different groups can be identified between 25
and 50 km. The classification between groups is mainly determined by
the vertical β range behaviour. If all comparison sensors show positive
relative bias with respect to the reference sensor, then we classify the
reference sensor as negative relative bias (β) range. Between 25
and 50 km for the latitude band of 30∘ S–30∘ N
(Fig. a), Group I consists of OSIRIS (balanced
β range), Group II includes GOMOS (low negative β range), Group
III includes MIPAS and SCIAMACHY (positive β range), and Group IV is SMR
(systematic negative β range).
The balanced β range means that differences to that instrument may be
positive or negative without
favouring any sign.
Most of the time, Group I (OSIRIS) shows a balanced behaviour with
statistically β values at the 95 % confidence level (i.e. |β|>2σβ) (See Fig. b).
For Group II, which consists of GOMOS, the absolute β values are not larger than ±15%.
GOMOS shows similarity with OSIRIS at 25 and 30 km.
In Group III (MIPAS, SCIAMACHY) the β range is mainly positive with respect to
the other sensors. Above 40 km, SCIAMACHY shows the largest
β value with respect to SMR of up to 20 % at 45 km
(see Fig. b). The values are statistically significant for
the majority of the comparison sensors.
Group IV consists of SMR with a negative β range with respect to all
comparison sensors.
Because of the low sampling of ACE-FTS in the tropics, there are only
two comparison sensors available, and therefore no general behaviour of ACE-FTS is possible. We observe a balanced
β range (Group I) behaviour at 30, 40, and at 45 km and a slightly positive β range (Group III)
at other altitudes.
From this plot we can conclude, that in the altitude range of 25 km,
most of the groups show similar behaviour in sign and β range to within
±10%. Highest variability is observed below 20 km
(>±20%). Between 25 and 45 km, sign and
range of β depends on the reference sensor with four distinct groups as
discussed before. Looking at Fig. b, one can
conclude that all β values that are larger
than ±10% are statistically significant.
At northern middle latitudes (30–60∘ N), SCIAMACHY changed its
behaviour between 25 and 35 km
(Fig. a). All other sensors show similar
behaviour as in the tropics.
The main difference to the tropics is seen at 20 km. Here, all sensors
present lower variability (<±12%) than in the tropics
and show balanced behaviour with the exception of SMR.
In the southern middle latitudes (30–60∘ S)
(Fig. a) the relative bias range resembles
the behaviour of the tropical band. ACE-FTS, on the other hand, performs as in
the northern middle latitudes. The variability below 20 km is however
smaller (<±20%) in comparison to the tropics.
There is no clear group behaviour for relative drift α in the tropics
30∘ S–30∘ N (see Fig. ).
Hereafter, we consider a drift estimate α to be statistically
significant if it is outside the ±2σα uncertainty interval
(non-shaded values Fig. b). At 40 km
the relative drift between OSIRIS and SMR is up to ±18 % decade-1 but is statistically non-significant.
A significant α value is observed for few combination pairs at different
altitudes. SMR shows significant values with respect to three instruments at
45 km and at 20 km. SCIAMACHY shows significant values with
respect to two instruments at 20 km (α<±20 % decade-1) and OSIRIS with two instruments at 35 km
(α<±5 % decade-1). For most of the
comparisons, no systematic significant relative drift is observed in this
latitude band.
In 30–60∘ N (Fig. a) the range of
α values is larger than in the tropics. Especially the instrument
pairs MIPAS/SCIAMACHY and SMR/ACE-FTS show α>±10 % decade-1. But these values are non-significant as it can
be seen in Fig. b with exception of
SMR/ACE-FTS at 35 and 50 km. SCIAMACHY shows significant values with
respect to OSIRIS between 20 and 40 km (α<±5 % decade-1) and OSIRIS with two instruments at 25 km
(α<±10 % decade-1).
In southern mid-latitudes (30–60∘ S) the α values are
largest below 25 km and smallest between 30 and 40 km
(Fig. a), but they are not statistically
significant (Fig. b). ACE-FTS shows
significant values with respect to three instruments at 25 km with
α<±15 % decade-1. SCIAMACHY shows
significant values with respect to two instruments at 50 km (α<±10 % decade-1). The total number of significant
values is lowest in this latitude band.
Only few statistically significant relative drift values are observed.
Generally 90 % of the pairs show non-significant relative drifts in
these three latitude bands at the described altitudes. Since the majority of the
pairs presented show no significant relative drift, we can conclude that
merging of the data sets from these six instruments is possible.
Such a drift analysis as carried out here can be helpful for identifying
outliers which could then be drift-corrected. In our case all instruments
show mostly statistically insignificant drift with respect to each other. In
the middle stratosphere the drifts are generally below
±6 % decade-1 (2σ), but can be higher in the upper
stratosphere and above, and in the lowermost stratosphere below about
20 km. When merging the data by simply taking averages from all
sensors as done in the last WMO (World Meteorological Organization) ozone
assessment , an additional uncertainty of about
3 % decade-1 (1σ) should be added to the physical trend
uncertainty derived from the linear trend regression to obtain a more
realistic estimate of the overall uncertainty.
Impact of local time and diurnal variation
The difference in local time of measurement can have an impact on the
differences in the collocated ozone profiles in the upper stratosphere
(above 40 km) . Following
the diurnal variation has the largest impact above
50 km with its difference between night-time and daytime of up to
±20 %. This might explain the variability observed in the
relative biases at 50 km but cannot explain the significant relative
biases observed for the altitudes below 50 km where the differences
in the local time are expected to have less than ±5 % impact on
the differences in ozone. We conclude that the variability observed in the
biases is intrinsical and instrument-dependent and not based on the
differences in local time.
Comparison to other validation results
Our results can be compared with other validation works
as discussed in the following.
performed a detailed drift analysis of MIPAS V5 220 to
derive a drift-corrected trend for the MIPAS ozone time series. We give an
overview of their results of drifts between MIPAS and OSIRIS and between
MIPAS and ACE-FTS. For the drifts between MIPAS and OSIRIS, they found mostly
negative statistically insignificant drifts in the upper stratosphere, with
negative statistically significant values in the northern middle latitudes.
The drift signs are in agreement with ours if we compare the MIPAS-OSIRIS
drifts in the Southern Hemisphere (as light blue squares in
Fig. ). They find statistically
insignificant positive drift values in the latitude bin of 30–40∘ S
between 40 and 48 km. We observe a positive drift at 40 and
50 km, respectively, that agrees qualitatively with their results.
The drifts are on the order of 2–5 % decade-1 going up to
±10 % decade-1 for lower altitudes and are insignificant, in
agreement with their findings. In the northern middle latitudes the drifts do not agree with our results. In our
case the drifts are non-significant and are positive, where in their results,
the drifts are negative and significant (see
Fig. b). The reason can arise from the
different time periods, i.e. 2005–2010 in our case and 2002–2010 in their
case and by neglecting quasi-biennial oscillation in our drift analysis.
For comparison between MIPAS and ACE-FTS, the sign of the drifts are
consistent with our results for the southern middle latitudes
30–60∘ S. Both papers observe non-significant drift in this
latitude band. On the other hand at 25 km we see a significant drift
between ACE-FTS and MIPAS which is not observed by . In
the northern middle latitude 30–60∘ N the dominating sign of the
drifts are negative in our case in agreement with their results above
22 km. Below this altitude we still observe a negative drift in
contrast to their findings.
made an analysis of differences between OSIRIS V5.07
and GOMOS V6 ozone profiles. In their comparison, mean relative difference
values for the tropical band are lower than 5 % between 20 and
40 km. At 40 km OSIRIS is lower than GOMOS by about
10 % in the tropics. In our case, the comparison between OSIRIS 5.01
and GOMOS V6 shows similar mean relative difference value and shape,
especially the sign and values of the mean relative difference between 20 and
40 km. The update of the ozone data led to the reduction of the mean
relative difference (compared to GOMOS V5) between the two instruments in
this specific region. The comparison of relative drift is in general
agreement, except at 45 km, where they observe a significant negative
drift, and we only see a positive non-significant drift between OSIRIS and
GOMOS. Significant drift values are only observed in the northern middle
latitudes 30–60∘ N below 25 km.
performed an individual trend analyses of three sensors
(MLS, SCIAMACHY, and OSIRIS). The results show a significant trend of
SCIAMACHY, MLS, and OSIRIS data at 35 km in the tropical latitude
band of 20∘ S–20∘ N. Their results are consistent with our
findings of significant relative drift between OSIRIS and SCIAMACHY at
35 km.
The methods applied here differ such that we used the mean
relative differences. The drifts given by are based on the
absolute differences and not on relative. provides
the drifts by using a robust method of the median values. Other validation
works are based on few pairs mainly from the perspective of a single
comparison sensor. A caveat to all methods (including ours) is that
non-linearity effects in biases and drifts can have an impact on the final
derived parameters.
Conclusions
Comparisons of ozone limb/occultation profiles between six independent
instruments from three platforms have been performed, i.e. from Envisat, Odin,
and SCISAT. The pairwise comparison using collocated data has been used to
establish the mean relative differences between 15 pairs of instruments.
Monthly mean relative difference time series have been used for the analysis
by applying a linear regression model on the differences. The two regression
parameters of the linear model, the slope α (relative drift) and the
intercept β (relative bias) for the reference time of February 2005
have been calculated for different altitudes and latitude bands. Between 25
and 50 km the β is within
±22% (in the majority of cases below ±10%). Large variability in the lowermost stratosphere
below 20 km is observed for all pairs in the tropics.
This can be explained by retrieval problems for sensors due to low signal to noise ratios, larger
natural variability, and
the impact of clouds and aerosols.
Overall, β can be sorted into different groups for reference sensors:
group I: OSIRIS (balanced β range)
group II: GOMOS (low negative β range)
group III: SCIAMACHY, MIPAS, and ACE-FTS (positive β range)
group IV: SMR (systematical negative β range)
The relative drifts between the various instruments can be quite large at
some altitudes, but because of the short data record (about 10 years), they
are mostly statistically insignificant.
Since 90 % of the pairs presented show no significant relative
drift, we can conclude that merging of the data sets from these six instruments is possible.
The evaluation of relative biases and relative drifts between pairwise
sensors demonstrates its value in understanding the differences between the
sensors and differences of the derived trends and can be used to estimate the
added uncertainty in physical trends from the drift. The added drift
uncertainty is estimated at about 3 % decade-1 (1σ).
The Supplement related to this article is available online at doi:10.5194/amt-8-4369-2015-supplement.
Acknowledgements
This work has been funded within the framework of the ESA project OZONE CCI (Climate Change Initiative).
We would like to thank the SCIAMACHY IUP-Bremen, MIPAS-IMK, GOMOS-FMI, OSIRIS, SMR, and
ACE-FTS groups for providing the data and support for this work. The ACE mission is supported primarily by
the Canadian Space Agency. The article processing charges for this open-access publication were covered by the University of Bremen.
Edited by: F. Khosrawi
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