MACC G-RG WP1 Task 1.5 (2.5)
10.05.2011
Validation of WP G-RG stratospheric trace gas services
Subtask: validation of offline models BASCOE, SACADA and TM3DAM
(Note: this report is linked to task 2.5: comparisons to IFS-MOZART)
Introduction ................................................................................................................................ 1
Process oriented validation..................................................................................................... 2
Sample episodes and coverage of data used for verification ................................................. 2
Data used by assimilation experiments .................................................................................. 2
Data-model configurations ..................................................................................................... 3
Diagnostics and metrics ......................................................................................................... 4
Summary of main results............................................................................................................ 4
Detailed analysis ........................................................................................................................ 7
Stratospheric Ozone in 1997, 2003 and 2009 ........................................................................ 7
56 hPa zonal mean ozone fields ......................................................................................... 7
Seasonal and Zonal Means..................................................................................................... 9
Mean distribution of H2O, CH4 and HCl in 2003 ........................................................... 11
Southern Hemisphere ........................................................................................................... 12
Background conditions..................................................................................................... 12
Antarctic ozone depletion................................................................................................. 14
Northern Hemisphere ........................................................................................................... 20
Background conditions..................................................................................................... 20
Ozone variability in low and high latitudes ..................................................................... 21
Appendix A .............................................................................................................................. 24
Data coverage ....................................................................................................................... 24
Appendix B .............................................................................................................................. 26
Scoring ................................................................................................................................. 26
References ................................................................................................................................ 33
Introduction
MACC G-RG WP 1 covers services for the provision of stratospheric trace gas observations
and model results based on level-2 1 assimilation. There exist also a service line for so called
level-2 products, which consists of retrieved tropospheric and stratospheric column data on
ozone, nitrogen dioxide, sulphur dioxide and formaldehyde. These products are not part of
this validation study. By focusing on the model results, the main goal of this effort is to
demonstrate the strength and weaknesses of the individual stratospheric model systems in
comparison to the IFS-MOZART.
The “Work plan for the validation of stratospheric trace gas services” [Lefever et al., 2010]
outlines the general concept. While task 1.5 covers the assimilation models BASCOE,
SACADA and TM3DAM, task 2.5 focuses on verification of IFS-MOZART. This
arrangement was originally made to highlight the differences between the independent models
BASCOE, SACADA and TM3DAM and the new C-IFS system. It was expected that
validation results could help in the decision which service should be continued and further
developed for operations in GAS (GMES Atmospheric Service). However, early results
showed that an ensemble of independent stratospheric models could better support the C-IFS
development than the commitment to a single system.
1
Level-2 in this context refers to atmospheric physical and chemical state parameters that are retrieved from
satellite measurements of the characteristic electromagnetic radiation spectrum (level-1).
Process oriented validation
Concerning the validation strategy, we refer to Eyring et al. [2005]. They discuss a more
process-oriented validation approach. While the focus is mainly on climate chemical models,
their findings are also relevant for assimilation systems based on offline chemistry-transport
models. The authors define several core processes and main areas of interest. Table 1 shows
an excerpt from the complete study with parameters and processes relevant for MACC G-RG.
In general three main areas of interest can be distinguished: Transport dominated processes,
chemistry dominated processes and processes that depend on the interaction between both
chemistry and transport. We will focus on the most relevant regions for ozone depletion, i.e.
the high northern and southern latitudes. Low latitudes will be discussed briefly w.r.t. the
distribution of source gases related to ozone chemistry.
Region
Subtropics and
high latitudes
Stratosphere
Tropics, UTLS
Polar latitudes
Midlatitudes
Process
Mixing barriers
Transport and
chemical partitioning
Troposph-stratosph.
vertical transport
Ozone depletion,
PSC activity
Ozone variability
Diagnostic
Latitudinal gradients
of long-lived tracers
Lat.-alt. distribution of
chemical reservoirs
Vertical gradients and
partitioning of species
Partitioning of species,
PSC surface area
Total ozone
Species
N2O, CH4, H2O,
CFC-11
ClONO2, HCl
O3, H2O, HCl
O3, HNO3, Clx, Cly,
NOx, NOy, PSCs
O3
Table 1: Core diagnostics and sample regions for stratospheric model evaluation
following Eyring et al. [2005].
Sample episodes and coverage of data used for verification
We focus on three sample years/episodes: 1997, 2003 April-December and 2009. This
selection was made to limit the data volume while analyzing a broad range of observed ozone
variability. Years under investigation differ considerably with respect to processes mentioned
in table 1, data assimilated by MACC stratospheric models (table 3) and coverage by
independent observations (table 2, see references therein). The analysis is binned w.r.t. polar
latitudes, mid-latitudes and tropics, i.e., 60°-90°, 30°-60° and +-30° latitude bands
respectively (see validation work plan for further details).
Instrument
HALOE [2011]
POAM3 [2011]
VINTERSOL [Harris & Amanatidis, 2003]
MLS-AURA [Waters et al., 2005]
Species
O3, H2O, CH4, HCl
O3
O3
O3, H2O, HNO3, HCl
Period
1997, 2003 Apr.-Dec.
2003 Apr.-Dec.
2003 Apr.-Dec.
2009
Table 2: Independent data sets (i.e., non-assimilated observations) used for the
evaluation of assimilation results. Note: VINTERSOL data consists of ozone sonde
observations gathered during the respective scientific campaign during 2002-2004.
Data used by assimilation experiments
Table 3 gives an overview of the satellite data used in the different assimilation systems.
Figures A1 and A2 show the yearly data coverage of all instruments applied by assimilation
models evaluated in this study. There’re two main groups of satellite instruments which have
to be distinguished: UV-backscatter and microwave instruments. While repeating rates for
individual locations are in general much higher for UV-instruments, microwave based sensors
show a better global coverage. MIPAS and MLS are able to resolve vertical trace gas profiles
with a vertical resolution between 3 and 10 km. SBUV gives coarse information on the
vertical ozone distribution and is part of the MSR data suit. GOME-2, TOMS and OMI only
provide total ozone data. Based on GOME-1, NNORSY retrievals [Müller et al., 2003] were
used for assimilation of 1997 ozone profiles.
Data-model configurations
While BASCOE and SACADA use both explicit gas phase and heterogeneous chemistry
[Errera, 2001; Elbern, 2010], TM3DAM applies a linear ozone chemistry scheme with an
additional parameterization for PSC conditions [van der A, 2010; Eskes et al., 2003]. Thus,
one has to be careful when comparing ozone results. Information on non-ozone species can,
of course, not be provided by TM3DAM.
Depending on the individual data-model configuration, type and spatio-temporal coverage of
assimilated data differs strongly between BASCOE, SACADA and TM3DAM. For example,
TM3DAM assimilates only data from UV-backscatter instruments. Therefore, respective
observations are limited to the sunlit areas. Generally, UV-instruments are limited to zenith
angles below 80°. All results close to the twilight zone have therefore to be investigated
carefully. Some measures of ozone depletion can be fairly misleading due to the impact of
model errors (e.g., estimates of the ozone-hole size). Results by SACADA and TM3DAM for
2009 are similar in so far as only total ozone (TOC) is assimilated. We will show that the type
of model constraint via the assimilated data has a strong influence on results. By far the best
overall coverage with respect to the number of observed chemical species and latitudinal
extension of observations is given by MIPAS. All six ESA standard species have been
assimilated by BASCOE and MIPAS during April-December 2003. This has to be taken into
account when discussing 2003 results. For the year 1997, UARS MLS limb ozone data were
applied for BASCOE, while for SACADA ozone profiles were assimilated based on ERS2GOME data. See figures A1 and A2 for an overview of the latitudinal data coverage.
Model
BASCOE
Instrument and species
MLS-UARS: O3
[Waters et al., 1999]
MIPAS:
Period
1997
2003 Apr-Dec
O3, H2O, HNO3, CH4, N2O, NO2
SACADA
[Carli et al., 2004]
ERS2-GOME/NNORSY]: O3
[Müller et al., 2003
MIPAS:
1997
2003 Apr-Dec
O3, H2O, HNO3, CH4, N2O, NO2
TM3DAM
[Carli et al., 2004]
GOME-2: TOC
[Loyola et al., 2011]
MSR: O3 [van der A, 2010]
MSR: O3 [van der A, 2010]
SCIAMACHY TOC
[Eskes et al., 2003]
2009
1997 (last day of month)
2003 (last day of month)
2009 (last day of month)
Table 3: The assimilation models evaluated in this study and their respective data
sources. Note, TOC=Total Ozone Column. For discussion of individual instruments and
data see references.
Diagnostics and metrics
According to the MACC GRG work plan for validation and scoring methods [Huijnen et al.,
2010], we use the agreed-on measures for systematic and random errors. For scoring with
respect to a reference model we use the reference skill score (see table 4). By definition this
score shows values between - and +1. Negative values in general indicate that the analysis is
even worse than the reference result. For the climatology SOCRATES V3 ten year data
[Brasseur, 1990] is applied. We use three base diagnostics: seasonal and yearly zonal means
for latitude-pressure depictions (species distribution), time records of daily vertical profiles
for certain stations (ozone variability) as well as daily snapshots and time records for the
56hPa model level (approximately 20 km altitude) to evaluate processes in the lower
stratosphere. (The 56hPa pressure value has been chosen for technical convenience). All
model results were interpolated to a common log-pressure grid (1.4 km steps) and reference
longitude-latitude horizontal mesh (2.5° by 3.75° increments) before comparing results.
Observations where allocated to altitude and horizontal bins by the nearest-neighbour method.
Diagnostic
56 hPa pressure level
Station profile time record
Seasonal zonal means
Short names
56 hPa
NM, NA, VN
Q1, Q2, Q3, Q4
Method
Log-pressure interpolation
Vertical profile above station
1/N ∑ ∑ fi for each quater
Table 4: Base diagnostics and respective notations used in this study. Vertical profiles
are derived for stations Neumayer (NM; 70.65°S, 8.26°E), Ny Alesund (NA; 78.93°N,
11.88°E) and Varanasi (VN; 25.32°N, 83.03°E). The double Sigma ∑ ∑ fi indicates a sum
over results fi for all longitudes and days available.
Definition / Full name
Fractional Gross Error
Normalized Mean Bias
Relative Skill Score
Combined Score
Acronym
FGE
NMB
RSS
CSC
Formula
2/N ∑|fi-oi|/|fi+oi|
2/N ∑ (fi-oi)/(fi+oi)
1 – FGEa / FGEc
(1-|NMB|)+(1-FGE)+RSS
Table 5: The main metrics used for scoring of model results. fi and oi designate model
analysis and observational values. FGEa and FGEc mean the fractonal gross error of the
analysis and the reference climatology respectively.
Summary of main results
We briefly summarize the most important findings. A detailed discussion with respect to the
relevant processes defined above is given in the following section 2. More diagrams and plots
can be found in the appendix B. Figure 1 gives an overview of the combined scores for all
assimilation results under consideration, covering the years 1997, 2003 and 2009. Note, that
this evaluation is limited to the altitude range 147hPa -0.32 hPa. The data-base, both for
assimilation and for validation, is critical when interpreting results. Therefore, appendix A
gives an overview of the respective spatio-temporal coverages. We summarize scoring results
as follows:
Relative ranking of models using combined scores
Using the combined scores, i.e., the sums of NMB, FGE and relative skill scores (RSS) to
rank all available ozone analyses (depending on the data-model configuration) for a certain
year, GOME-SACADA 1997 and MIPAS-SACADA/BASCOE 2003 show clearly superior
results (figure 1). Differences between MIPAS-SACADA and MIPAS-BASCOE 2003 are
small (<1%). The contribution of the RSS to the combined score is rather small (<20%). 1997
MSR-TM3DAM and GOME2-SACADA 2009 results show no skill at all (noqte, no
BASCOE data was available for 2009). Figure B1 shows a more detailed comparison of the
relative size of NMB and FGE values. While the NMB numbers are limited within a 10%
range, respective FGE values are considerably higher and can reach even 20% in some cases.
Differences between model results depending on year, latitude, height and input data
Because the data-base was different between individual model runs (with the exception of
2003 SACADA-BASCOE results), it is not possible to attribute differences to models or data
only. However, models show a clearly different performance w.r.t. to latitude band and
altitude range when different input data is assimilated. This is especially evident when
comparing MLS-BASCOE and GOME-SACADA 1997 results (e.g., figure 2a). The coverage
by MLS-AURA ozone was especially pour during September 1997 leading to a weaker
ozone-hole in the BASCOE analysis. On the other hand, as indicated by figure 1, SACADA
and BASCOE results are quite similar when the same assimilation data (MIPAS ESA 2003) is
used. Independent of the input data, all models perform in general better in higher latitudes
and show less skill in the upper stratosphere. Ozone in this height region is especially poor
reproduced by TM3DAM 1997 and SACADA 2009, with a strong underestimation above 5
hPa. This may hint at systematic model deficiencies but could also be due to a lack of vertical
profile information in the input data (in SACADA 2009 TOC -assimilation only) and an illdefined-observational operator.
Non-ozone species
Evaluation of non-ozone species was possible for BASCOE and SACADA (explicit
stratospheric chemistry schemes). Daily CH4, H2O and HCl results for April-December,
2003, and also 1997 for SACADA, were evaluated in comparison to collocated HALOE
observations. Figure 5 shows a general good correspondence for the assimilated species CH4
and H2O, while HCl (non-assimilated) is significantly deteriorated in the MIPAS-SACADA
2003 analysis, especially in the upper stratosphere and the south polar vortex. In the same
height region, H2O is significantly increased by MIPAS H2O assimilation. Because, in the
free run (no assimilation), HCl compares much better to HALOE observations, we suspect
excessive HCl depletion via H20+O(1D) 2OH, HCl+OH  Cl+H2O. Evaluation of
respective BASCOE results is pending. If HCl depletion via H2O assimilation is confirmed,
involved reaction rates should be verified. On the other hand, this finding highlights the
possibility of chemical imbalances triggered by 4D-Var assimilation.
2009
#728952
20090131, 20090228,
20090331, 20090430,
20090531, 20090630,
20090731, 20090831,
20090930, 20091031,
20091130, 20091231
2003
#9779
20030331, 20030430,
20030531, 20030630,
20030731, 20030831,
20030930, 20031031,
20031130, 20031231
1997
#7947
19970131, 19970228,
19970331, 19970430,
19970630, 19970731,
19970831, 19970930,
19971031, 19971130,
19971231
Figure 1: Combined scores for all analysis results considered. Colour boxes show
results of individual scores, i.e., NMB, FGE and RSS, for a certain model type
and year. The info boxes at the right show the total number of independent
observations (#) and the dates used (YYYYMMDD) for the years indicated. Note
the missing BASCOE data for 2009. Because SOCRATES (SOC3) is the
reference, no RSS is calculated for SOC3. SAC17 and SAC20 indicate SACADA
model versions 1.7 and 2.0 respectively.
Detailed analysis
The detailed analysis focuses on the high southern and northern latitude ozone using profile
records and 56hPa results to compare the observed and model-based variability. Seasonal and
zonal means are used to evaluate seasonal changes of ozone and related source gases with
latitude and altitude. We start each discussion with background information on the
meteorological and chemical characteristics for the periods of interest 1997, 2003 and 2009.
Stratospheric Ozone in 1997, 2003 and 2009
56 hPa zonal mean ozone fields
To give an overview of the performances of BASCOE and SACADA within the lower
stratosphere, figures 2a and 2b show the respective daily zonal mean ozone mixing ratio in 56
hPa for 1997, 2003. Figure 2c shows a comparison to MLS-AURA data for 2009. For 2003,
differences are quite small, which was expected from the application of MIPAS data in both
systems. Differences in 1997 are more significant. Especially in high latitudes coverage by
MLS-UARS (BASCOE) is far worse (see figures A1 and A2) compared to GOME
(SACADA). As a consequence, in 1997, BASCOE underestimates the ozone depletion in both
northern winter and Antarctic spring.
Figure 2a: Time record of zonal-mean 56 hPa ozone for 1997 based on MLSBASCOE (top) and GOME-SACADA (bottom) results.
Figure 2b: Time record of zonal-mean 56 hPa ozone for 2003 based on MIPASBASCOE (top) and MIPAS-SACADA (bottom) results.
In 2009, GOME2-SACADA compares qualitatively well to MLS-AURA. The timing of the
Antarctic ozone hole is well captured by the analysis. However, summer-zone in high
latitudes is overestimated leading to a too shallow hole. Figure B7 shows the total NMB
values for 2009 depending on latitude and altitude. It shows a systematic error pattern with
too high ozone in the lower stratosphere increasing with latitude and a strong underestimation
above 40km altitude. We will discuss additional MLS-comparisons for HCl and HNO3 in
section “Antarctic Ozone Depletion).
Figure 2c: Time record of zonal-mean 56 hPa ozone for 2009 based on GOME2SACADA (top) results and MLS-AURA observations (bottom).
Seasonal and Zonal Means
Stratospheric trace gases in polar and high latitudes are characterized by strong variability due
to dynamical and chemical processes. Within the Tropics conditions are more stable (e.g., less
variation of solar insolation). The tropics are also the global source region for ozone and
important reservoir gases related to ozone depletion in higher latitudes. Due to data available
we limit our discussion to H2O, CH4 and HCl. These gases are observed by satellite
instruments and analysis of their mean distribution can highlight model issues with transport
and chemical partitioning. Figure 4 shows the seasonal mean distributions as observed by
HALOE. The CH4 distribution reflects meridional transport and depletion of CH4 in the
stratosphere. HCl is an important Cl reservoir and is involved in gas phase and heterogeneous
ozone depletion. As HCl is mostly generated in the upper stratosphere its vertical distribution
is inverted compared to CH4, which is of tropospheric origin. The horizontal gradients of
CH4 indicate the presence of so called mixing barriers. Regions with extremely low
temperatures above the tropopause show also minimum H2O mixing ratios. Elevated H2O
values in general indicate tropospheric-stratospheric transport. An important H2O source in
the upper stratosphere is CH4 oxidation.
Figure 4: Seasonal mean distributions of ozone, CH4, H2O and HCl based on HALOE
observations for the fourth quarter (Q4) of 2003.
2
2
1
1
0
0
8
8
4
4
0
0
3
3
2
2
1
1
0
0
Figure 5: Seasonal mean distributions of CH4, H2O and HCl as calculated by
SACADA and BASCOE using MIPAS data for the fourth quarter (Q4) of 2003. Note:
SACADA HCl (third row) is compared to a SACADA free run (no assimilation).
Mean distribution of H2O, CH4 and HCl in 2003
The vertical distribution of sources and sinks of H2O, CH4 and HCl is in general well known.
As chemical reactants they are strongly interconnected, e.g., HCl is produced via the Cl+CH4
reaction, while it is depleted by reactions with OH, which can be formed by photolysis of
H2O. Comparing their distribution to observations can help to identify model deficiencies
with respect to chemical partitioning, meridional transport, lower boundary conditions and
mixing barriers. We here compare HALOE observations to SACADA and BASCOE results
based on MIPAS 2003 data. Note that MIPAS provides H2O and CH4 observations, which
were actively assimilated by both models.
Figures 4 and 5 show seasonal mean distributions of CH4, H2O and HCl based on HALOE
observations and MIPAS assimilation by BASCOE and SACADA for Q4, 2003. For CH4 and
H2O, apart from the troposphere, the observed mean distributions are reproduced quiet well
by both models. However, a strong HCl deficit develops during the SACADA experiment
throughout the lower mesosphere while the southern polar maximum in Q4 is overestimated.
The HCl deficit is not visible in the free run shown by figure 5 for comparison. Respective
HCl results for the years 1979 (GOME-1 input data) and 2009 (GOME-2 input data) much
better agree with observations. Thus, the HCl deficit must be due to assimilation of non-ozone
species in the MIPAS experiment. Results from the free run show significantly higher CH4
values in the lower Mesosphere and during ozone-hole conditions while H2O is slightly
decreased compared to HALOE and MIPAS. In summary, correction of model CH4 and H2O
fields may lead to a strong reduction of HCl. Further analysis, especially of respective
BASCOE results is ongoing.
To better understand the MIPAS-SACADA HCl 2003 deficit,a case study without HCl
assimilation and comparisons to respective BASCOE results would be helpful.
Southern Hemisphere
Background conditions
Contrary to the high ozone variability generally observed at high northern latitudes, the
Antarctic stratosphere is usually dominated by a much less disturbed strong polar vortex with
persistent low temperatures during winter and early spring. Figure 6 shows records of the total
area size for ozone values below 220 DU for the years 1997, 2003 and 2009. This area can be
used as an indicator for the strength of chemical ozone depletion. Spatial coverage and
distribution of areas with minimum ozone levels can vary quiet considerably inter-annually
and between years depending on stratospheric dynamics and its influence on chemistry.
Figure 7 shows the 56 hPa temperature and the corresponding analyzed ozone record above
the Neumayer Station at 70.4°S and 8.2°W. While 2003 and 2009 show a very similar
behaviour with continuously decreasing temperatures from April until August and persistent
low temperatures until the end of September, in 1997, variations of temperature and ozone
Figure 6: Ozone hole size for the years 1997, 2003 and 2009 (source:
http://www.temis.nl/protocols/o3hole/index.php).
were much more pronounced. Also, the vertical area with temperatures below 190K was
considerable smaller (not shown). Further analysis of the horizontal vortex structure shows
that it was much more elongated and distorted in 1997 compared to 2003 and 2009. On some
days model ozone levels nearly drop to zero as shown by figure 7. In this case, the analyzed
loss during end of July was found to be due to an almost complete ClONO2+HCl uptake by
sulphate aerosols in the model. A re-analysis with decreased uptake coefficients showed
higher ozone values without a byte-out.
Figure 7: 56hPa Ozone concentrations (above) and Temperatures (below)
above Neumayer Station (70.4°S and 8.2°W) for the years 1997, 2003 and
2009 based on ECMWF analyses. Ozone values are based on SACADA
Figure 8: Time records of ozone concentration profiles above Neumayer Station
between April and December, 2003, based on MIPAS-BASCOE (top) and MIPASSACADA (mid) results. Below, respective results for a free SACADA run (no
assimilation) are shown.
Antarctic ozone depletion
We focus on the 2003 ozone hole episode covered by the complete chemistry models
SACADA and BASCOE. CH4 and HCl results will be complemented by a 2009 HCl and
HNO3 comparison to MLS-AURA. Figure 8 shows time records of SACADA and BASCOE
ozone profiles above Neumayer Station (70.65°S 8.26°W) for 2003 based on MIPAS
observations. Additionally, results of a free SACADA run are shown. Both models derive
similar minimum ozone values during October, 2003. However, ozone depletion is
Figure 9: Time records of ozone concentration bases on MIPAS-SACADA (top),
MIPAS-BASCOE (mid) and ozone sonde observations above Neumayer Station
from August, 23rd, until November, 2003.
Figure 10: Time record of CH4 profile changes above Neumayer Station between
April and December, 2003. The two top level plots show MIPAS-BASCOE and
MIPAS-SACADA results while the bottom plot depicts respective results for a
free SACADA run (no assimilation).
significantly stronger as analyzed by the SACADA run. The free run shows comparable
depletion rates, but a different timing with minimum values early in September. Figure 9
compares September-November results to corresponding ozone soundings. Duration and
intensity of ozone depletion is better matched by SACADA results, while the lower
stratosphere/tropopause region is better reproduced by BASCOE results.
Figure 10 shows the change of CH4 mixing ratio from April until December 2003. In contrast
to the free run (no assimilation) the stratospheric CH4 decline during Antarctic spring is much
more pronounced in MIPAS-SACADA and MIPAS-BASCOE results. Note that CH4 levels
are ca. 20% in the lower stratosphere due to MIPAS assimilation (not shown). Thus
partitioning between chemically passive and active species is also expected to be different.
Figure 11: Time records of HNO3 mixing ratios from MIPAS-BASCOE (top) and
MIPAS-SACADA (bottom) analyses above Neumayer Station between April and
December, 2003.
This is at least confirmed for HCl by figures 12. Clearly, HCl depletion due to heterogeneous
chemistry during Antarctic summer is much weaker in the MIPAS-SACADA run with a
strong HCl increase in September/October. As the results for Q4 in 2003 show (figure 5), HCl
is significantly overestimated by MIPAS-SACADA during this period. This may be partly
due to an underestimation of lower-stratospheric ozone. Exaggerated CH4 (compared to
HALOE) can serve as another possible HCl-source. Finally, figure 11 shows a comparison of
BASCOE and SACADA HNO3, again for Neumayer Station. Though the same MIPAS
HNO3 data is assimilated, significant differences occur during summer/spring 2003. With a
stronger and earlier ozone depletion, SACADA also shows smaller HNO3 mixing ratios in the
lowermost stratosphere. Another distinctive feature in SACADA results is a descending layer
with elevated HNO3 valuesin the upper stratosphere. A similar effect is barely visible in CH4
(figure 10). Because this feature is not visible in BASCOE results, an indirect effect due to
CH4/H2O assimilation seems more likely (note, N2O and NO2 are both constraint by
MIPAS). E.g., a local increase of the OH concentration via H2O + O(1D) may lead to a
temporary surge in HNO3.
Figure 12: Time records of HCL mixing ratios based on MIPAS-SACADA (top),
and a SACADA free run (no assimilation) above Neumayer Station from August,
23rd, until November, 2003.
We close the discussion of BASCOE and SACADA results related to Antarctic ozone
depletion with a comparison of 2009 GOME2-SACADA HCl and HNO3 to AURA-MLS.
Figure 13 shows time records of zonal mean ozone profiles south of 60°S. (Note the poor
sample rate with only one day per month – see figure 1.) A weak overestimation of HCl is
now only visible during July. The onset of denitrification due to PSC activity results in a
underestimation of HNO3 in the lower stratosphere. Compared to MLS, ozone depletion is
generally too weak and Cl + CH4 reaction is enhanced. Thus, HCl is underestimated during
September and October 2009. In spite of these deficits, HCl results for 2009 seem more
reliable than for 2003. More detailed analyses of the different performances of BASCOE and
SACADA in 2003 and 2009 is necessary to better understand the relevant processes and to
better discriminate between model biases and direct assimilation effects.
Figure 13: Comparison od MLS-AURA to GOME2-SACADA time records of
ozone (top), HCl (mid) and HNO3 (bottom) for latitudes >60°S in 2009.
Northern Hemisphere
Background conditions
With respect to ozone depletion on the Northern Hemisphere (NH), figure 1 shows that
February total ozone levels were lowest for 1997 and highest in 2009. Analysis by Tilmes at
al. [2004] showed considerable ozone loss within the vortex area for 1997 and 2003. In
January 2009, the early break-down of the polar vortex allowed sustained transport of ozone
rich air into high latitudes. In both 1997 and 2003 areas with minimum February total ozone
values were located over the Northern Atlantic/ Polar Ocean and Northern Scandinavia, while
the same area showed the highest values in February 2009. Chemical ozone depletion was
exceptional high during early 1997 [Tilmes at al., 2004] with record low temperatures in the
lower stratosphere as indicated by figure 2. The same figure shows the well-known
correlation between ozone concentration and temperatures. Temperatures below
approximately 195K trigger Polar Stratospheric Clouds (PSCs) within the lower Stratosphere.
Though PSC area is much more limited in the NH compared to the Southern Hemisphere
(SH), Chlorine activation due to PSCs and respective chemical ozone depletion can reach
comparable size. Thus, ozone chemistry during spring in high latitudes of both hemispheres
shows a lot of similarities. We will use the same indicators for NH and SH.
Figure 14: Mean monthly total ozone fields in the northern hemisphere for February
1997, 2003 and 2009 (source KNMI TEMIS).
Figure 15: 56hPa Ozone concentration and Temperature over Ny Alesund Station
(78.9°N, 11.9°W) for the years 1997 (black) and 2009 (green).
Ozone variability in low and high latitudes
We discuss briefly 1997 and 2009 results for Ny-Alesund Station (78°55'N, 11°56'E) and
Varanasi (25° 20' N, 83° 00' E). As mentioned above, during 1997, comparatively strong
ozone depletion was observed during northern polar winter, while in 2009, ozone levels
stayed relative high due to a strong stratospheric warming in late January (see figure 15).
Figure 16 shows that the 1997 ozone is better reproduced by GOME-SACADA. Here again,
as already discussed for the Antarctic ozone hole, the poor MLS coverage hampers BASCOE
assimilation and proves as an insufficient constraint for polar ozone.
As a sample for sub-tropical ozone, Figure 17 depicts the GOME2-SACADA ozone
concentration profile above Varanasi (India). As expected, inter-annual variability is much
reduced compared to higher latitudes, though ozone is temporarily decreased during winter
months. This behaviour is well captured by the model. As figure 18 shows, lower
stratospheric ozone is slightly underestimated during this period compared to MLS-AURA
observations. However, as the sample results for Ny-Alesund illuminate, the general ozone
bias in high latitudes (too high near 10 hPa, too low above) is much more pronounced.
Figure 16: Ozone time records of MLS-BASOE and GOME2-SACADA 1997 (top).
Below, respective results for GOME2_SACADA and MLS-AURA 2009 above NyAlesund Station for 2009.
Figure 17: Time record of GOME2-SACADA (top) and MLS-AURA (below)
ozone profiles above Varanasi Station for 2009.
Figure 18: Differences of ozone mixing ratios between SACADA and MLS for
2009 above Neumayer (top) and Varanasi Station (below).
Appendix A
Data coverage
Figure A1: Latitudinal coverage of MIPAS-UARS observations in
1997. Boxes indicate minimum and maximum latitudes and duration
of south- and northward looking measurement modes. A yaw
manoeuvre took place approx. every 36 days. The maximum
numbers of scans per day was 1319. The right axis shows the total
number of observing days per box. Note: yaw days are not included.
Figure A2: Yearly coverage of GOME/NNORSY (top), MIPAS (mid) and
GOME-2 (bottom instruments used for assimilation experiments of 1997,
2003 and 2009 respectively. The red lines indicate the minimum and
maximum latitudes observed. The blue lines represent the number of
observations per day.
Appendix B
Scoring
1997
2003
2009
Figure B1: Combined NMB and FGE scores of analysis results for the years
1997, 2003 and 2009.
1997
MLS-BASCOE
GOME-SACADA
MSR-TM3DAM
Figure B2: Relative Skill Score (RSS) for ozone analyses in 1997 based on
BASCOE, SACADA and TM3DAM.
2003
MIPAS-BASCOE
MIPAS-SACADA
MSR-TM3DAM
Figure B3: Relative Skill Score (RSS) for ozone analyses in 2003 based on
BASCOE, SACADA and TM3DAM.
2009
GOME2-SACADA
SCIAMACHYTM3DAM
Figure B4: Relative Skill Score (RSS) for ozone analyses in 2009 based on
SACADA and TM3DAM.
1997
MLS-BASCOE
GOME-SACADA
MSR-TM3DAM
Figure B5: Normalized Mean Bias (NMB) for ozone analyses in 1997 based on
BASCOE, SACADA and TM3DAM.
2003
MIPAS-BASCOE
MIPAS-SACADA
MSR-TM3DAM
Figure B6: Normalized Mean Bias (NMB) for ozone analyses in 2003 based on
BASCOE, SACADA and TM3DAM.
2009
GOME2-SACADA
SCIAMACHYTM3DAM
Figure B7: Normalized Mean Bias (NMB) for ozone analyses in 2009 based on
SACADA and TM3DAM.
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