C-IFS-CB05-BASCOE: Stratospheric Chemistry in the Integrated Forecasting System of ECMWF

We present a model description and benchmark evaluation of an extension of the tropospheric chemistry module in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) with stratospheric chemistry, referred to as C-IFS-CB05-BASCOE (for brevity here referred to as C-IFS-TS). The stratospheric chemistry originates from the one used in the Belgian Assimilation System for Chemical ObsErvations (BASCOE), and is here combined with the modified CB05 chemistry module for the troposphere as currently used operationally in the 15 Copernicus Atmosphere Monitoring Service (CAMS). In our approach either the tropospheric or stratospheric chemistry module is applied depending on the altitude of each individual grid box with respect to the tropopause. An evaluation of a 1.5 year long C-IFS-TS simulation indicates good performance of the system in terms of stratospheric ozone, nitrogen dioxide as well as other reactive tracers in comparison to various satellite retrieval products. This marks a first step towards a chemistry module within IFS that encompasses both tropospheric and stratospheric composition. 20

, and from implications of sudden stratospheric warmings on circulation patterns (Manney et al., 2015) to general radiative feedbacks of ozone, water vapor and CO2 on weather and climate (Solomon et al., 2010).
These aspects have long been studied in the framework of Chemistry Transport Models (CTMs) and, more recently, in GCMs, see, e.g., the SPARC Chemistry-Climate Model Validation Activity (CCMVal, 2010). In GCMs the role of stratospheric ozone chemistry on the tropospheric climate can explicitly be studied (e.g. Scaife et al., 2011). But also 5 meteorological models can benefit from having a good representation of the stratospheric composition and its variability, considering the radiative effects and the resulting impact on stratospheric as well as tropospheric temperatures (Monge-Sanz et al., 2013), which becomes relevant for tropospheric forecast skills on long-range to seasonal time scales (Maycock et al., 2011).
Within a series of MACC (Monitoring Atmospheric Composition and Climate) European research projects a global forecast 10 and assimilation system has been built, which is the core for the global system of the Copernicus Atmosphere Monitoring Service, (CAMS, http://atmosphere.copernicus.eu ). In CAMS, forecasts of atmospheric composition are carried out , Morcrette et al., 2009, Engelen et al. 2009), which benefit from assimilation of satellite retrievals , Benedetti et al., 2009, to improve the initial conditions for composition fields in terms of reactive gases, aerosols and greenhouse gases. Here a tropospheric chemistry scheme has been embedded in ECMWF's Integrated Forecast 15 System, referred to as Composition-IFS (C-IFS, . Even though the current operational version of C-IFS based on the Carbon Bond chemistry scheme (CB05) provides good model capability on tropospheric composition , the stratosphere is only realistically constrained in terms of ozone. This is because so far the model ozone is based on a linear scheme (Cariolle and Tyssèdre, 2007) which is suitable owing to the data-assimilation capabilities of C-IFS of both total column and profile satellite retrievals Lefever et al., 2015). 20 Also it is recognized that the applicability of radiation feedbacks of tracer fields, such as ozone and water vapor, as produced through CH4 oxidation, are hampered by schemes that are based on linearizations (Cariolle and Morcrette, 2006;de Grandpré et al., 2009), due to their intrinsic dependencies to climatologies which are used to construct such schemes and hence may behave poorly in anomalous situations. Having full stratospheric chemistry available in the IFS therefore would not only allow to study a wider range of atmospheric composition processes, but also a more independent assessment of radiation 25 feedbacks on temperature, hence providing the potential for improvements in stratospheric and tropospheric meteorology.
These considerations drive the need for extension of C-IFS with a module for stratospheric chemistry. For this we use the chemistry scheme from the Belgian Assimilation System for Chemical ObsErvations (BASCOE), Errera et al. (2008), which was developed to assimilate satellite observations of stratospheric composition. assimilation system GEM, demonstrating the potential of a coupled chemical-dynamical assimilation system for stratospheric studies (de Grandpré et al., 2009;Robichaud et al., 2010). BASCOE has been used and evaluated within the framework of MACC as an independent system for the provision of Near Real-Time analyses of stratospheric ozone and for the validation of the corresponding product by the main assimilation system (Lefever et al., 2015;.
We have developed a strategy for merging the CB05 tropospheric chemistry scheme and the stratospheric chemistry scheme 5 used in BASCOE within C-IFS. An assessment of the two chemistry schemes showed that there is only partial overlap in tracers and reactions that are essential in both regimes. For instance, 15 out of the full list of 99 tracers need to be treated in the chemical mechanisms for both troposphere and stratosphere. Also the modelling of the photolysis rates and heterogeneous reactions have been optimized for application in troposphere and stratosphere separately. Therefore we did not aim at a full integration of the chemistry schemes, but rather choose a flexible setup where -within a single framework-10 either the tropospheric or stratospheric chemistry modules are addressed.
In this paper we describe our modeling strategy and provide a benchmark evaluation of the merged C-IFS-TS system with focus on the stratospheric composition. The paper is organized as follows: In Sect 2 the chemistry modules for the stratosphere are described and the merging with the tropospheric scheme is explained.. Section 3 provides details on the setup of the model runs, and the observational data used for the model evaluation. Section 4 provides a basic model 15 evaluation of the system. We finalize this manuscript with conclusions and an outlook for further work.

Atmospheric chemistry in C-IFS
For general aspects related to chemistry modeling in the C-IFS the reader is referred to . The   meteorological  model  in  the  current  version  of  C-IFS  is  based  on  IFS  cycle  41r1 (http://www.ecmwf.int/en/forecasts/documentation-and-support/changes-ecmwf-model). The advection is simulated with a 20 three-dimensional semi-Lagrangian advection scheme, which applies a quasi-monotonic cubic interpolation of the departure values.
In the following two subsections we describe the C-IFS modules for the stratospheric (referred to as BASCOE) and tropospheric (CB05) chemistry parameterizations, continued by a section describing the merging procedure of these two modules to form the C-IFS-TS system. The full list of trace gases is given in Table A1 in the Appendix, including the 25 domains where they are actively treated within the chemistry.

Stratospheric chemistry
From the BASCOE system (Errera et al., 2008) the chemical scheme and the parameterization for Polar Stratospheric Clouds (PSC) has been implemented in the C-IFS. The BASCOE chemical scheme used here is labelled "sb14a". It includes 58 species interacting through 142 gas-phase, 9 heterogeneous and 52 photolytic reactions. This chemical scheme merges the 30 reaction lists developed by Errera and Fonteyn (2001) to produce short-term analyses, with the list included in the Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-40, 2016 Manuscript under review for journal Geosci. Model Dev. Published: 7 March 2016 c Author(s) 2016. CC-BY 3.0 License.
SOCRATES 2-D model for long-term studies of the middle atmosphere (Brasseur et al., 2000;Chabrillat and Fonteyn, 2003). The resulting list of species (see Table A1) includes all the ozone-depleting substances and greenhouse gases necessary for multi-decadal simulations of the couplings between dynamics and chemistry in the stratosphere, as well as the reservoir and short-lived species necessary for a complete description of stratospheric ozone photochemistry.
Gas-phase and heterogeneous reaction rates are taken from JPL evaluation 17 (Sander et al., 2011) and JPL evaluation 13 5 (Sander et al., 2000), respectively. Lookup tables of photolysis rates were computed offline by the TUV package (Madronich and Flocke, 1999) as a function of log-pressure altitude, ozone overhead column and solar zenith angle. The photolysis tables used in chemical scheme sb14a are based on absorption cross-sections from JPL evaluation 15 .
The kinetic rates for heterogeneous chemistry are determined by the parameterization of Fonteyn and Larsen (1996), using classical expressions for the uptake coefficients on sulfate aerosols (Hanson and Ravishankara, 1994) and on Polar 10 Stratospheric Clouds (PSCs) (Sander et al., 2000).
The surface area density of stratospheric aerosols uses the same climatology as Daerden et al. (2007), while the surface area densities of PSCs is computed from a simple cold-point parameterization. Ice PSCs are presumed to exist at any grid point in the winter/spring polar regions where the temperature is colder than 186 K, and Nitric Acid Tri-hydrate (NAT) PSCs where the temperature is colder than 194 K. The surface area density is set to 10 −6 cm 2 /cm 3 for ice PSCs and 10 −7 cm 2 /cm 3 for NAT 15 PSCs. The sedimentation of PSC particles causes denitrification and dehydration. This process is approximated by an exponential decay of HNO3 with a characteristic time-scale of 100 days for gridpoints where NAT particles are supposed to exist, and an exponential decay of HNO3 and H2O with a characteristic time-scale of 9 days for gridpoints where ice particles are supposed to exist.
Mass mixing ratios for N2O, CO2 and a selection of anthropogenic and organic halogenic trace gases are constrained at the 20 surface by a global mean constant value, Table 1. Assuming that trace gases are well mixed in the troposphere, this essentially serves as lower boundary conditions for the stratospheric chemistry.

Tropospheric chemistry
The tropospheric chemistry in the C-IFS is based on the CB05 mechanism (Yarwood et al., 2005). It adopts a lumping approach for organic species by defining a separate tracer species for specific types of functional groups. The scheme has 25 been modified and extended to include an explicit treatment of C1 to C3 species as described in Williams et al., (2013), and SO2, di-methyl sulphide (DMS), methyl sulphonic acid (MSA) and ammonia (NH3) (Huijnen et al., 2010). A coupling to the MACC aerosol model is available (Huijnen et al., 2014), but not switched on for this study. The reaction rates follow the recommendations given in either Sander et al. (2011) or Atkinson et al. (2006). The modified band approach (MBA), which is adopted for the computation of photolysis rates (Williams et al., 2012), uses 7 absorption bands across the spectral range 30 202 − 695 nm. At instances of large solar zenith angles (71-85°) a different set of band intervals is used. In the MBA the radiative transfer calculation using the absorption and scattering components introduced by gases, aerosols and clouds is computed on-line for each of the predefined band intervals. The complete chemical mechanism as applied for the Geosci. Model Dev. Discuss., doi: 10.5194/gmd-2016-40, 2016 Manuscript under review for journal Geosci. Model Dev. troposphere is extensively documented in . A specification of the emissions and deposition of tropospheric reactive trace gases is provided as well.

Merging procedure for the tropospheric and stratospheric chemistry
In this section we describe the strategy for merging the chemistry modules for the troposphere and stratosphere to form the C-IFS-TS system. Key chemical cycles differ between troposphere and stratosphere, hence requiring different 5 parameterizations. For example, the oxidation of non-methane hydrocarbons (NMHC's) is essentially taking place in the troposphere and represents an important driver for tropospheric O3 production. The chemical evolution of PAN and organic nitrate can be neglected in the stratosphere. On the other hand, N2O and CFC's are essentially chemically inactive in the troposphere and will only photolyse by UV radiation in the stratosphere. Therefore, only the transport of those trace gases needs to be accounted for in the troposphere. Associated chemistry involving single atom radicals, such as N, O, Br, Cl, can 10 only be produced in the stratosphere. Also the parameterization of the photolysis rates leads to different requirements for the troposphere and stratosphere, as will be discussed in the next subsection. Finally the numerical solver of the chemical mechanism contributes substantially to the total costs of the model run in terms of run-time, depending on the size of the reaction mechanism. These elements have motivated us to divide the chemistry in the C-IFS-TS system into a tropospheric and stratospheric part. Note that there is only one set of transported atmospheric trace gases and only the position of the grid 15 box above or below the tropopause determines if the tropospheric or stratospheric chemistry is applied.
The tropopause can be defined based on a different criteria. A common approach is to use dynamical criterion such as the isentropic potential vorticity (e.g., Thuburn and Craig, 1997) but this fails in regions of small absolute vorticity, notably in the tropics. A definition based on the lapse rate (WMO, 1957) is an alternative, but may not be well defined in the presence of multiple stable layers. We therefore choose to base our criterion on the chemical composition of the atmosphere 20 considering that the tropopause is associated with sharp gradients in trace gases (e.g., Gaudel et al., 2015). This has the advantage that parcels with tropospheric/stratospheric composition can be traced dynamically, and the most appropriate chemistry scheme can be adopted to it. In our simulation we use a chemical definition of the tropopause level, where tropospheric grid cells are defined at O3<200 ppb and CO>40 ppb, for P > 40 hPa.
For both troposphere (CB05) and stratosphere (BASCOE) the numerical solver is generated using the Kinetic Pre-Processor 25 (KPP, Sandu and Sander, 2006) software. Specificaly we adopt the standard four-stages, third order Rosenbrock solver (Rodas3). This is different from the hard-coded Eulerian backward implicit solver as used in , and is motivated by the improved coding flexibility and accuracy.
Most of the gas phase reactions that take place both in the troposphere and stratosphere, such as NOx and HOx reactions, are simulated in identical ways in both chemistry schemes. It is worth mentioning that the tracers O 1 D and O 3 P, produced from 30 O3 and O2 photolysis, are described implicitly in the troposphere, while they are treated explicitly in the stratosphere. For trace gases whose chemistry is currently neglected in the stratosphere (the NMHC's, PAN, Organic nitrate, SO2) we adopt a 10-day decay rate to prevent spurious accumulation of these tracers in the stratosphere. Note that tropospheric halogen The three options to run this type of C-IFS experiments and the computational cost are given in Table 2. As compared to the C-IFS-T experiments, the costs of running an experiment including full stratospheric chemistry with the C-IFS-TS system have increased by ~50%. The additional burden for transport due to the increase in the number of tracers only marginally increases the computational time, because of the efficiency of the semi-Lagrangian advection for multiple tracers. A test 10 experiment where tropospheric and stratospheric chemistry were merged into a single reaction mechanism, where all reactions are activated in the whole atmosphere, led to an increase in costs by ~50% compared to C-IFS-TS, indicating the benefit of having separate solver codes for tropospheric and stratospheric chemistry. Finally this also allows for an easy switch between system setups.

Merging photolysis rates 15
For parameterization of the photolysis rates the Modified Band Approach (MBA, Williams et al., 2012) and the lookup table approach (Errera and Fonteyn, 2001) as have been optimized in the past for applications in the troposphere and stratosphere are retained, see Table 3. While for tropospheric conditions scattering and absorption properties of clouds and aerosol strongly impact the magnitude of photolysis rates and hence the local chemical composition, this is of less relevance in the stratosphere. Wavelengths shorter than 202 nm, on the other hand, are largely blocked by stratospheric ozone and oxygen 20 and do not contribute to radiation in the troposphere (Williams et al., 2012). At higher altitudes these short wavelengths contribute to the Chapman cycle and to the break down of CH4, CFC's and N2O either directly or through oxidation by O 1 D.
Also the presence of sunlight at solar zenith angles (SZA) larger than 90° at high altitudes needs to be accounted for in the stratosphere but not necessarily in the troposphere. Solar radiation reaches the stratosphere earlier than the Earth's surface, due to the Earth's curvature which, amongst others, triggers the polar spring stratospheric ozone depletion. 25 Table 4 lists the photolysis rates that are active both in the troposphere and stratosphere. Photolysis rates for reactions occurring both in the troposphere and stratosphere are merged at the interface, in order to ensure a smooth transition between the two schemes. This is done by an interpolation at four model levels around the interface level between both parameterizations, for SZA<85°. For larger SZA the original value for the photolysis rate is retained in case of stratospheric chemistry, while it is switched off for the troposphere. 30 Note that even though the reaction rates have been merged, the products from the same photolytic reactions are sometimes different as a consequence of the different reaction mechanisms between the troposphere and stratosphere.
An example of the merging strategy is given in Fig. 1. It shows that at the interface for J O3 and J NO2 on average a small increase of the merged photolysis rate is seen towards lower altitudes, with the switch to MBA in the troposphere, which is a consequence of the combination of differences in the parameterizations. Even though such jumps are undesirable, no visible impact on local chemical composition was found.

Merging tracer transport 5
Tracer transport is treated identically for all individual chemical tracers. Since the semi-Lagrangian advection does not formally conserve mass  a global mass fixer is applied (Diamantakis and Flemming, 2014) to all but a few tracers, including NO, NO2 and H2O. Rather than conserving mass during the advection step of the individual components NO and NO2, this is enforced to a stratospheric NOx tracer defined as the sum of NO and NO2. While a chemical H2O tracer is defined in the full atmosphere, in the troposphere H2O mass mixing ratios are constrained by the 10 humidity (q) simulated in the meteorological model in the IFS. Stratospheric H2O (i.e. above the tropopause level) is governed by chemical production and loss. Stratospheric H2O mass is not strictly conserved considering that the global advection errors essentially originate from the tropospheric part (where by far most H2O mass is located with large spatial gradients), and should not affect the stratospheric H2O mass budget (where total mass is much lower and H2O mixing ratio gradients are much smoother). 15

Model setup and observations used
We have executed a run of C-IFS-TS for the period April 2008 until December 2009. Stratospheric ozone in C-IFS-TS is further compared to that of the C-IFS-T system  which uses the ECMWF standard linear ozone scheme (version 2a, Cariolle and Teyssèdre, 2007) in the stratosphere.
We have initialized C-IFS-TS and CIFS-T runs on 1 April 2008 using assimilated concentration fields from the BASCOE 20 system in the stratosphere for this date. The horizontal resolution of these runs is T255 (i.e. approx. 0.7° lon / lat) with 60 levels in the vertical. Meteorology is relaxed towards ERA-Interim.
The performance of C-IFS-TS has further been compared against the BASCOE-CTM (without data assimilation), using the same chemical mechanism and parameterizations as implemented in the C-IFS. The BASCOE-CTM is run with a resolution of 1.0° lon / lat similar to the resolution of C-IFS used here, and on the same vertical grid of 60 levels. It uses temperature, 25 pressure and wind fields simulated by the C-IFS runs. Using the same dynamical fields together with an identical implementation of the chemistry code should allow to identify differences in the transport schemes between C-IFS and the BASCOE-CTM. Common chemical biases between both systems also point at issues in the chemical parameterization.

Observational data used for validation
We evaluate C-IFS-TS in terms of stratospheric O3, NO2, N2O, CH4, H2O and HCl, and for this purpose use a range of observation-based products.
Total column O3 is validated against KNMI's multi sensor reanalysis version 2 (MSR, van der A et al., 2015) which, for the 2008-2009 time period is based on Solar Backscattering Ultraviolet radiometer (SBUV/2), Global Ozone Monitoring 5 Experiment (GOME), SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) and Ozone Monitoring Instrument (OMI) observations. The satellite retrieval products used in the MSR are bias-corrected with respect to Brewer and Dobson Spectrophotometers to remove discrepancies between the different satellite data sets. The uncertainty in the product, as quantified by the bias of the observation-minus-analysis statistics, is in general less than 1 DU.
O3 profiles are compared to ozonesonde data that are acquired from the World Ozone and Ultaviolet radiation Data Centre 10 (WOUDC). The precision of the ozonesondes is on the order of 5% in the stratosphere (Hassler et al., 2015), when based on electrochemical concentration cell (ECC) devices (~85% of all soundings). Larger random errors ( This is a high spectral resolution Fourier transform spectrometer operating with a Michelson interferometer. Vertical profiles of atmospheric volume mixing ratios of trace constituents are retrieved from the occultation spectra, as described in Boone et al. (2005), with a vertical resolution of 3-4 km at maximum. Here we use level 2 retrievals (version 3.0) of N2O and CH4. 30 ACE-FTS N2O observations between 6 and 30 km are within ±15% compared against independent observations, while above they agree to within ±4 ppbv (Strong et al., 2008). The uncertainty in ACE-FTS CH4 observations is within 10% in the upper Model results are also compared with observations of O3 (Ceccherini et al., 2008), HNO3 (Wang et al., 2007) and NO2 (Wetzel et al., 2007) retrieved from limb emission spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the European satellite Envisat, and with observations of H2O (Read et al., 2007) 5 and HCl (Froidevaux et al., 2008) retrieved from the Microwave Limb Sounder (MLS) onboard the satellite Aura.
MIPAS random and systematic errors for various trace gases are reported by Raspollini et al. (2013). For NO2 between 25 and 50 km altitude these are below 10 and 20% respectively. For HNO3 between 15 and 30 km, these are below 8 and 15% while for O3 between 20 and 55 these are below 5 and 10%. At 15 km, these errors increase to 10 and 20%, respectively. The MLS error budget is reported in Livesey et al. (2011). For HCl observations between 1-20 hPa the precision and accuracy are 10 below 10 and 15% respectively. Between 46 and 100 hPa, these are below 0.3 and 0.2 ppbv, respectively. For H2O between 0.46 and 100 hPa, precision and accuracy are below 15 and 8%. Closer inspection of O3 profiles against sondes averaged over the NH-mid latitudes, tropics and SH-mid latitudes for the DJF and JJA seasons (Figures 3 and 4) also shows reduced biases most prominently visible at the 10-30 hPa altitude range in the sub-tropics for C-IFS-TS. Nevertheless, this experiment still shows a positive bias near the ozone maximum in terms of partial pressure (~50 hPa) and also at lower altitudes during the northern hemispheric spring season. In the tropics the use of the full stratospheric chemistry implies a slight degradation against the linear scheme around the ozone maximum, where the 25 Cariolle parameterization is very well tuned while the negative bias in the lower stratosphere, as also found in C-IFS-T, is not improved. The assessment of NO2 against MIPAS daytime NO2 observations, acquired by sampling the ascending orbits from Envisat, shows good agreement with both models. Also the C-IFS-TS describes well the seasonal variation in zonal mean stratospheric NO2 columns at different latitude bands, Fig. 7, with monthly mean biases with respect to the SCIAMACHY observations of less than ±0.5 × 10 15 molec cm -2 in the tropics and at mid-latitudes.

Model evaluation
However, a positive NO2 bias with respect to night-time MIPAS NO2 observations appears larger for C-IFS-TS than for the 5 BASCOE-CTM (Fig. 6). In contrast, this figure also shows a negative bias in HNO3 with respect to MIPAS observations in both the BASCOE-CTM and C-IFS-TS, again more marked in the C-IFS experiment. Considering that daytime NO2 bias in C-IFS-TS is small and similar to that for BASCOE-CTM, the larger negative bias in C-IFS HNO3 is likely not caused by biases in its chemical precursors. which is also rather similar as found in the BASCOE-CTM control run. Even though the absolute difference between C-IFS N2O and observations from MIPAS and MLS is somewhat different in absolute terms than found for the evaluation against 15 ACE-FTS, the general features are very similar.
At lower altitudes (100-10 hPa) C-IFS-TS N2O and CH4 shows larger discrepancies to the observations, and to the BASCOE-CTM run with an over-estimation most prominently around 30 hPa in the tropics and SH-mid latitudes, suggesting too much vertical transport within the middle and lower stratosphere. This feature could also contribute to the positive biases seen in O3 at ~20 hPa in Figures 3 and 4. 20 Fig. 9 shows a good consistency between H2O modelled by C-IFS-TS and the BASCOE-CTM results, albeit with a slight negative bias with respect to MLS observations above 5 hPa, and a positive bias around 30 hPa in the tropics, associated with corresponding biases in CH4. This figure also shows globally a good agreement between HCl modelled by C-IFS-TS and MLS observations, although with a positive bias of 0.8 ppbv confined in the region of ozone depletion above Antarctica.

Conclusions 25
We have presented a model description and benchmark evaluation of an extension of the C-IFS system with stratospheric ozone chemistry of the BASCOE model added to the already existing tropospheric scheme CB05, referred to as C-IFS-CB05-BASCOE, or C-IFS-TS in short. In our approach we have retained a separate treatment for tropospheric and stratospheric chemistry, and select the most appropriate scheme depending on the altitude with respect to the tropopause level. This has the advantage that parameterizations which are optimized for tropospheric and stratospheric chemistry, 30 respectively, can be retained, which also substantially reduces the computational costs of the chemical solver compared to an approach where all reactions are activated in the whole atmosphere. Also, it allows for an easy switch between system Geosci. Model Dev. Discuss., doi: 10.5194/gmd-2016-40, 2016 Manuscript under review for journal Geosci. Model Dev. setups. To avoid jumps in tracer concentrations at the interface the consistency in gas-phase reaction rates has been verified while the photolysis rates from the two parameterizations are interpolated across the interface.
An evaluation of a 1.5 year simulation of C-IFS-TS indicates good performance of the system in terms of stratospheric ozone, of similar quality as BASCOE-CTM model results. The O3 total columns show biases mostly smaller than ±20 DU when compared to the MSR-v2. Also the profiles were generally well captured, and show an improvement with respect to 5 the C-IFS-T linear ozone scheme in the stratosphere over mid-latitudes. The depth and variability of the ozone hole over Antarctica is modelled well.
Also evaluation of other trace gases (NO2, HNO3, CH4, N2O, HCl) against observations derived from various satellite retrievals (SCIAMACHY, ACE-FTS, MIPAS, MLS) indicates a good performance. But for CH4 and N2O a larger error with respect to limb-sounding retrievals was found at around 30 hPa than the BASCOE-CTM. This could point at too fast vertical 10 transport within the middle and lower stratosphere in the C-IFS framework.
This benchmark model evaluation of C-IFS-TS marks a first step towards merging tropospheric and stratospheric chemistry within IFS, aiming at daily operational forecasts of composition for the entire atmosphere. Future work will focus on the following aspects: -Chemical data-assimilation: initial tests with data-assimilation of O3 total column and profile retrievals suggest that 15 stratospheric ozone is successfully constrained in C-IFS-TS. However, observational constraints on other components driving ozone chemistry are currently lacking in the assimilation system. Our extension opens the possibility for assimilation of additional tracers such as N2O and HCl. However, for the 4D-VAR assimilation of short-lived species such as NO2 and ClO an adjoint chemistry module would be required as implemented the BASCOE DA system.
-Alignment of the reaction mechanism and photolysis rates: while at current stage the gas-phase and photolytic reaction 20 rates of the parent schemes are retained, we foresee a further integration to ensure better alignment of the chemical mechanisms. Especially the existing jumps in photolysis rates as a consequence of the different parameterizations are not desirable, even though they are not harmful for model stability nor visibly lead to any degradation in model performance.
The alignment in terms of gas-phase reaction rate expressions can be achieved by the introduction of the KPP solver in C-IFS, for both tropospheric and stratospheric chemistry, which allows for a better traceable model development than the hard-25 coded Euler Backward Integration solver as adopted in .
-Extension of tropospheric and stratospheric chemistry schemes: the availability of a comprehensive set of tracer fields allows for a relatively easy extension of the tropospheric reaction mechanism by including selective reactions originating from the stratospheric chemistry, and vice versa. Examples are the introduction of halogen chemistry in the troposphere (von Glasow and Crutzen, 2007), or SO2 conversion to sulphate aerosol in the stratosphere, relevant in case of strong volcanic 30 events (Bândă, et al., 2015).
-Optimization of solver efficiency: even though the use of KPP has simplified the code maintenance and may result in a higher numerical accuracy of the solution, it also caused a considerable slow-down of the numerical efficiency as compared to the Euler Backward Integration solver, as that solver had been optimized for tropospheric ozone chemistry in C- IFS-Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-40, 2016 Manuscript under review for journal Geosci. Model Dev. Published: 7 March 2016 c Author(s) 2016. CC-BY 3.0 License.
CB05. Solutions could be an optimization of the initial chemical time step for the KPP solver, depending on prevailing chemical and physical conditions, and an optimization of the automated solver code, which allows for a more efficient code structure (KP4, Jöckel et al., 2010).
In summary, the extension towards stratospheric chemistry in C-IFS broadens its ability for forecast and assimilation of stratospheric composition, which is beneficial to the monitoring capabilities in CAMS, and may also contribute to advances 5 in meteorological forecasting of the ECMWF IFS model in the future.

Code availability
The C-IFS source code is integrated into ECWMF's IFS code, which is available subject to a licence agreement with ECMWF, see also  for details. The stratospheric chemistry module of C-IFS was originally developed in the framework of BASCOE. Readers interested in the BASCOE code can contact the developers through 10 http://bascoe.oma.be. Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-40, 2016 Manuscript under review for journal Geosci. Model Dev. Published: 7 March 2016 c Author(s) 2016. CC-BY 3.0 License.  Table 3. Parameterization of photolysis rates for troposphere (CB05-based) and stratosphere (BASCOE-based) Troposphere (Williams et al., 2012) Stratosphere (Errera and Fonteyn, 2001) No. J-rates 18 52