N02 and ozone observations from space and the prospect for ...At emission areas the N02 concentration will peak at the surface, while downstream of such areas the pollution plume will

N02 and ozone observations from space and theprospect for chemical forecasting

H.J. Eskes & H.M, KelderRoyal Nethei-lands Meteorological Institute,POBOX 201, 3730 AE De Bilt, The Netherlands,

Abstract

A tropospheric chemical forecast system should consist of a reliable descriptionof the dynamical state of the atmosphere, measurements of the global distribu-tion of key chemicals, and realistic emission scenarios. New satellite missions

such as Envisat will provide unique information on the columns of several keytropospheric species, e.g. ozone, N02, HCHO, CO, CH4. In this paper we willdiscuss difficulties in the retrieval of quantitative tropospheric columns of tracegases such as N02 from GOME and SCIAMACHY satellite observations, A newintegrated retrieval/modelling approach for tropospheric N02 is discussed. Sec-

ondly, an operational bzone forecast scheme is presented. This system providesmeaningful ozone and clear-sky UV distributions for a forecast period of about sixdays, and can be viewed as a first step towards a chemical fhrecast system,

1 Introduction

For a successful chemical forecast several requirements have to be fhlfilled. First,a state-of-the-art forecast model is needed. This model should be initialised byassimilating satellite and in-situ measurements of the dyna~ical state of the atmos-

phere, i.e. it should consist of chemical modules coupled (directly or off-line) toa numerical weather prediction model, As a second requirement, a realistic global

(or regional) analysis of the chemical state of the atmosphere has to be constructed,This analysis should be based on as many high-quality chemical observations aspossible. Since ground based observations are limited in number (they typicallyconsist of ground stations in developed countries measuring surface concentra-tions), observations from satellites with a global coverage are to be preferred.Unfortunately, not many reliable quantitative measurements of tropospheric trace

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452 Air pollution X

gases by satellites exist today, Furthermore, the model should contain a reliable up-to-date emission inventory, This inventory should be consistent with the availablemeasurements.

In this paper we will focus on two issues related to chemical forecasting, Inthe first section we will discuss satellite observations of NOZ made by the GOME

instrument. Satellite observations of N02 and other key tropospheric trace gases

will be important input for a future chemical data assimilation system, and willallow top-down estimates of emissions. The problems related to the satellite retriev-al of quantitative N02 tropospheric column amounts will be discussed, and analternative combined retrieval/modelling approach will be presented, In the sec-ond section we will present an operational ozone forecasting system [4, 5] basedon Global Ozone Monitoring Experiment (GOME) near-real-time ozone columns,

An important step towards filling the gap in our knowledge of tropospheric NO.[3] has been made by the GOME instrument on ERS-2 [2]. The prime advantage

of satellites is their capability of providing a fill global mapping of the atmo-spheric composition [1]. After cloud filtering, GOME provides global coverageN02 maps roughly every week. Column amounts of N02 can be derived from the

detailed spectral information provided by GOME in the wavelength range 420-450 nm. Good signal to noise ratio’s (of about 20) are obtained for N02 with theDifferential Optical Absorption Spectroscopy (DOAS) retrieval technique. This isrelated to the absence of strong other absorbers (e.g. ozone) in this spectral inter-

val, GOME has demonstrated the ability to observe boundary layer N02: on top of

a stratospheric background enhanced column N02 amounts are observed that cor-relate well with known industrialised areas [12, 10], GOME has also detected N02

plumes originating from biomass burning events. Furthermore, there are signaturesof lightning-produced N02 in the GOME data set,

Ozone is an important trace gas for numerical weather forecasts. It has a stronginfluence on the temperature and dynamics in the atmosphere, and a knowledge ofozone may improve satellite retrievals, especially the radiation modelling for theTOVS instruments. In recent years, techniques have been dqveloped for the assim-ilation of ozone in several numerical weather forecast models and in chemistry-transport models, Institutes involved include the European Centre for MediumRange Weather Forecast (ECMWF) and National Oceanic and Atmospheric Admin-istration (NOAA). ECMWF ozone forecasts, based on near-real time satellite ozonedata, will become available in the near future. NOAA has recently started to pro-

vide ozone forecasts based on assimilated operational Solar Backscatter UV datafrom the NOAA satellites, In this paper we describe an operational ozone forecast-ing system developed at the Royal Netherlands Meteorological Institute (KNMI),

based on GOME ozone data and a chemistry transport model driven by ECMWFforecasts of the meteorological fields.


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2 Tropospheric NOZ from GOME observations

2,1 Retrieval of tropospheric N02

A major challenge is the derivation of accurate quantitative tropospheric NOZ col-umn amounts for individual ground pixels based on satellite data, The retrieval

of tropospheric trace gas species is characterised by large uncertainties, related toclouds, the surface albedo, the trace gas profile, the stratospheric column of NOQ,and aerosols [10, 11, 12, 9]:● The largest uncertainties are due to clouds, as they will shield near-surface NOZ

from the view of the satellite, The retrieval depends very sensitively on the pres-

ence of clouds, and even small cloud fractions (between 5 to 20°/0) have a majorimpact. High quality observations of the cloud properties (at least cloud fractionand cloud top height) are necessary for a quantitative retrieval,

● The surface albedo directly influences the sensitivity of GOME for boundarylayer N02, High quality albedo maps in the relevant spectral range are essential.

● Profiles of N02 are characterised by a large range of variability. At emission

areas the N02 concentration will peak at the surface, while downstream of suchareas the pollution plume will peak at higher altitudes. The profile of N02 willbe determined by aspects like the distribution of emission sources, the stabilityand height of the boundary layer, wet removal of nitric acid, deep convectionand long-range transport by the wind. All these aspects are strongly varying in

time and space.● The N02 columns measured by GOME consist of comparable stratospheric and

tropospheric contributions. The stratospheric background has to be quantified

carefully in order to derive the tropospheric column, Atmospheric dynamics iswell known to generate significant variability in stratospheric tracer amounts,consistent with for instance HALOE observations of N02, A standard approachapplied to GOME is based on the assumption that stratospheric NOZ is zonallyuniform, or at least has only a small longitudinal variatiqn. Such simplificationmakes the retrieval of small tropospheric N02 columns practically impossible.

● Another source of uncertainty are aerosols. Thick aerosol layers influence theradiation field and the sensitivity of GOME for near-surface N02,

A disadvantage of the GOME instrument is the large ground pixel size of 320

by 40 km. These long strips limit the ability of GOME to resolve small scale NOQemission areas, such as places with heavy industry, towns or biomass burning sites.The large pixel size implies considerable retrieval uncertainties related to clouds -

as a result of the large pixel area the ii-action of pixels that I’S(nearly) cloud free isvery small, Future satellite instruments such as SCIAMACHY on ENVISAT, andOMI on EOS-AURA will have smaller footprints and will ‘improve this issue.

2.2 Combined retrieval/modelling approach

Over the past years a new approach for the determination of tropospheric N02 hasbeen developed. This approach consists of a combination of retrieval and mod-


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elling. The main motivation for this new approach is to improve uncertaintiesrelated to the five retrieval issues listed above. The TM3 chemistry-transport model(CTM), driven by high-quality meteorological fields, is used to provide best-guessprofiles of N02, based on the latest emission inventories, atmospheric transport,photochemistry, lightning modelling and wet/dry removal processes [7]. The useof a CTM is further motivated by the good correspondence between the modelled

and the GOME observed geographical distribution of NOZ [14].The approach consists of the following steps: The model forecast fields, based

on realistic 6h meteorological fields obtained from the ECMWF, are collocatedwith the GOME observations. The radiative transfer modelling in the retrieval isperformed based on this model trace gas profile and temperature profile. The tem-perature dependence of the cross section of NOZ is accounted for. The modelledstratospheric N02 distribution is employed to derive a tropospheric column by sub-tracting a modelled (or assimilated) stratosphere from the measured column. Withthis step we can account for N02 fine structure related to stratospheric dynam-ics. The retrieval is fhrtherrnore coupled to cloud top height and cloud fractionretrievals derived from the GOME data with the Fresco algorithm [8], Monthly

albedo maps are constructed from TOMS and GOME observations [6] [Koelemei-jer, private communications]. An approach similar in spirit has been developedrecently by Martin and co-workers [11].

2.3 N02 results

As an example we show a monthly-mean NOZ map for March 1997, This mapis derived based on the GOME Data Processor version 2,7 slant column amounts,profile estimates from the TM3 chemist~-transport model and cloud fraction andcloud top pressures from the Fresco algorithm, as described above.

Figure 1 demonstrates some of the issues discussed above. The top panel showsthe derived total column by assuming that all the N02 is in the stratosphere, and inthe lower panel we have used the modelled N02 profiles in the radiative transfer

calculation. The figure shows the ability of GOME to observe the major emissionareas of NOZ in the world, and the data can be confronted with model predictions[14].

In the figure we have only included pixels with an estimated cloud fraction lessthat 30V0. However, even with this pre-selection it is quite essential to account forthe remaining cloud fraction. The reason is the high albedo Iof the cloud compared

to the surface, For instance, for a cloud fraction of only ld-20% the clouded partof the pixel (which shields the boundary layer from view) may have the same con-tribution to the signal as the cloud-free part. Neglecting even small cloud fractions

can lead to significant errors for the tropospheric column.The differences between the first two panels demonstrate that large errors are

to be expected when a wrong profile shape is used, For instance, the use of asingle climatological profile for the whole Earth in the retrieval is very crude:tropospheric N02 is known to vary several orders of magnitude as a function of


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Figure I: Vertical column of N02 for the month March 1997, derived from themeasurements of GOME, Top panel: retrieval based on the assumptionthat all the N02 is in the stratosphere, Bottom panel: retrieval based on

profiles taken from the TM3 CTM.

the geographical position and time. This implies that the model plays a large rolein obtaining the results in this figure. This is unfortunate, but can not be avoided.

This profile dependence is a major motivation for using a model in the retrievalto improve upon a simple climatology. The retrieval is especially sensitive to theratio between the tropospheric and stratospheric column.

One approach to reduce the sensitivity to this ratio is to first subtract an esti-mated stratospheric background, and subsequently perform a retrieval for the remain-


456 Air pollution X

ing GOME signal [10, 12]. The figure suggests that the monthly-mean strato-

spheric background (blue-green colours) is close to zonally symmetric, and thatthe column at 180 degree longitude is a reasonable estimate. This approach has

been used by several groups, However, just like in the case of ozone, the strato-spheric N02 column shows significant dynamical variation, Neglecting this vari-ation makes it essentially impossible to distinguish smaller tropospheric columnsfrom the stratospheric background. One may improve on this by assimilating theGOME observations in a model with realistic stratospheric dynamics, and this isthe approach that we follow, The remaining tropospheric column can be estimatedbased on a modelled tropospheric profile shape,

The approach outlined above defines an “observation operator” for GOME N02:a forward model which computes a model prediction of the GOME radiances basedon the model state. Such an observation operator is an essential building block ofan assimilation (and forecasting) system.

To conclude: the quantitative N02 tropospheric column estimate depends strong-ly on assumption on the profile shape and the stratospheric contribution to the

total column. Clouds should be treated explicitly and accurate albedo maps arenecessary, Simplified assumptions on these aspects can easily lead to troposphericcolumn errors of 50- 10OOAfor individual pixels,

3 Ozone forecasts

3.1 Model setup

The ozone forecasts are based on a tracer-transport and assimilation model calledTM3DAM. The modelling of the transport, chemistry and the aspects of the ozone

data assimilation are described in more detail in a recent paper [4]. Here we willonly provide a brief overview of the model setup.

The three-dimensional advection of ozone is described by the flux-based second

order moments scheme of Prather, The model follows the new ECMWF verticallayer definition, operational from the end of 1999 until the present. The 60 hybridlayers between 0,1 hPa and the surface have been reduced to 44 by removing 16

layers in the lower and middle troposphere, and above 300 hPa the layers in themodel coincide with the ECMWF layers. The horizontal resolution of the modelversion used in this study is 2.5 by 2.5 degree, The model is driven by 6-hourlymeteorological fields from the European Centre for Medium-Range Weather Fore-

casts (ECMWF) model.

Ozone chemistry is described by two parametrization, ~ne is a linearization ofthe gas-phase ozone chemistry, in which ozone is dependipg on a source-sink, theozone amount, temperature and UV radiation, A second parametrization scheme

accounts for heterogeneous ozone loss, This second scheme introduces an addi-tional chlorine activation tracer which is formed when the temperature drops belowthe critical temperature of polar stratospheric cloud formation,

The total ozone data is assimilated in TM3DAM based on a simplified Kalmanfilter technique. This approach produces detailed and realistic time- and space-


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dependent forecast error distributions, Several aspects of the error modelling app-roach have been discussed in [4].

3.2 Observations

The ozone analysis is based on total column ozone observations measured by the

GOME instrument. A discussion of the ozone products and retrieval techniquescan be found in [2]. For ozone forecasting purposes a near-real time product isessential, The data assimilation results described here are based on the fast deliv-

ery total ozone columns [13]. The GOME measurements are collected and ozonecolumns are retrieval within 3 hours after the measurements are made.

3.3 Ozone forecasts

The GOME ozone assimilation and forecast approach outlined above is operational(on a best-effort basis) since Autumn 2000, Five-day ozone forecast are producedeach day. These forecasts and a data base of ozone fields is provided via the website of the KNMI, http://www.knmi, nl/gome-fd,

3.3.1 Forecast performanceFor numerical weather prediction models it is common practice to measure theforecast performance with the anomaly correlation (AC) function. This function

measures the amount of agreement between the n-day forecast anomaly (= differ-

ence between forecast and climatology) and the analysis or verification anomaly,which is produced n days later. Normally the 500 hPa geopotential height is used(or wind field near the equator) as quantity for which the anomaly correlationis determined, Normally AC > 0.6 is considered a useful forecast, The forecastperiod for which AC becomes 0,6 in the Northern midlatitudes is presently about7 days for the ECMWF model. In recent years also the Southern hemisphere andthe tropics have shown a rapid improvement, approaching the forecast skill in theNorthern hemisphere,

For the ozone forecast system we have studied the total ozone “anomaly” withrespect to a running monthly mean total ozone distribution [5], Note the difference

between ozone and the geopotential: the ozone column is and integrated quantity,and is sensitive to vertical motions. Furthermore, most of the ozone anomaly iscaused by transport in the lower stratosphere, while numerical weather forecastskills are based on tropospheric quantities, Ozone is a trace+r,and apart from large

‘(scale features there are pronounced small scale anomalies filaments),For the Northern and Southern mid- and high-latitude regions we find a correla-

tion function which crosses 0.6 after about 6 days. This is an encouraging resultssince this is very comparable to the ECMWF geopotential scores (note that thereis a delay of about half a day between the ECMWF forecast run and the ozoneforecast run). It demonstrates that usefid ozone and clear-sky UV forecasts can beproduced up to one week in advance.

The tropics is quite a different case: the AC reaches 0.6 after about 2 to 2.5 days.


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3–day forecast

mmmmaammmmmmmnn<150 176Z002252602753003263503’~B400426460476~500 DU

Analysis

mmmmnDmanammwan<150176 ZOO225260275300 S25850375400426460475 ~1500DU

Figure 2: The first large low-ozone episode of the winter 2001-2002, on 9 Novem-

ber 2001, Top: 3-day forecast, Bottom: Verification.


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There are several reasons to be identified for this contrast with mid and high lati-

tudes. First remember that we have defined the anomaly as the difference betweenthe ozone column and the monthly mean. These anomalies are very small near the

equator, between 2 and 3 0/0of the total column ! This implies that random noise inthe GOME observations (which is estimated to be of this order), but also retrieval

dependence on e.g. clouds, have a significant negative influence on the skill, Next,most of the ozone variability in the tropics can be attributed to the troposphere,in contrast to the extratropics. Since the model does not account for troposphericchemistry, we can not expect excellent scores at low latitudes.

3.3.2 ExamplesNovember and December of 2001 was a very active mini-ozone hole period. Withthe ozone forecast system we could successfully predict the occurrence of theselow-ozone episodes well before they occurred. In Figure 2 we show a 3-day fore-cast of the first pronounced event on November 9. The verification shows that the

ozone distribution in the forecast is close to what is actually observed, The corre-sponding five-day forecast also showed a low-ozone region at the same position,but somewhat less pronounced and with a somewhat different shape.

Other examples of useful forecasts are related to the South Pole ozone hole,The final break-up of the ozone hole is normally determined by the atmosphericflow. The breakup event of 19 November 2000 was correctly predicted four daysin advance [5]. Excursions of the ozone hole to lower latitudes and over inhabitedland (e.g. South America) occurred several times in the last years, When these

events occur later in the season (October-November), the solar zenith angle maybe such that extreme UV doses may occur, as shown in Figure 3.

4 Conclusions and outlook.. . .. .,,. A.

A future chemical forecast system should be based on extended high-quality tro-pospheric data sets, a reliable model for the dynamics and chemistry of the atmos-phere, and detailed emission inventories. Data sets provided by GOME, and futureinstruments like SCIAMACHY on ENVISAT and OMI on EOS-CHEM have thepotential to provide important input for such a system. These instruments willprovide measurements of ozone, N02, CH4, CO, HCHO and S02, These are the

important key species of tropospheric chemistry, The data sets enable top-downemission estimates and can be used as input for chemical data assimilation,

Despite these prospects, the retrieval of reliable troposp~c column estimatesfor these species based on the space observations remains a major challenge, We

have discussed difficulties in the retrieval of N02, Given the strong dependence

of the retrieval on a-priori information, we recommend a combined modelling-retrieval approach, An observation operator has been constructed for N02 obser-vations from GOME, SCIAMACHY or OMI. This contains multiple scatteringradiative transfer, cloud fraction and cloud top height, temperature corrections anddetailed albedo maps. Such an observation operator is an essential ingredient forchemical data assimilation.


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Figure 3: Global map of the clear-sky UV index on 12 October 2000. The high UVvalues over South America are related to excursions of the ozone hole.

A first step towards chemical forecasting is the assimilation and forecasting ofozone. We have discussed the results of an operational forecast system developedat the KNMI. Meaningful forecast can be made up to 6-7 days in advance, which isan encouraging result, Examples of forecast include the occurrence of ozone miniholes over the northern Atlantic and Europe, and the variability and breakup ofthe ozone hole. The forecasts are available on http://www.k~mi, nl/gome.fd. In thenear future the ozone assimilation will be extended with ozone profile informationfrom GOME and SCIAMACHY. With this we hope improve the knowledge on

tropospheric ozone.

References

[1] Borrell, P., Burrows, J,P., Platt, U., & Zehner, C., Det~rmining Tropospheric

Concentrations of Trace Gases from Space, ESA bulletin, 107, pp. 72–81,2001.

[2] Burrows, J.P. et al,, The Global Ozone Monitoring Exeriment (GOME): Mis-sion concept and first scientific results, J, Atmos. Sci,, 56, 151-175, 1999.

[3] Emmons, L. K., et al., Climatologies of NO. and NOV: A comparison of dataand models, Atoms, Environ., 31, 1851-1904, 1997.

[4] Eskes, H. J., van Velthoven, P, F, J,, Valks, P, J. M, & Kelder, H, M., Assimila-tion of GOME total ozone satellite observations in a three-dimensional tracer


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transport model, preprint 2002.

[5] Eskes, H, J,, van Velthoven, P, F. J,, & Kelder, H. M., Ozone forecasts,preprint 2002,

[6] Heman, J,R,, &Celatier, E, A,, Eatisurface reflectivity climatology at34O-380 nm from TOMS data, J. Geophys,Res., 102,28003-28011, 1997.

[7] Houweling, S., Dentener, F., & Lelieveld, J,, The impact of non-methane

hydrocarbon compounds on tropospheric photo-chemistry, J! Geophys.Res.,103, 10673, 1998,

[8] Koelemeijer, R,B,A,, Stammes, P,, Hovenier, J.W., & de Haan, J.F., A fastmethod for retrieval of cloud parameters using oxygen A-band measurementsfrom Global Ozone Monitoring Experiment, J, Geophys.Res., 106, 3475-3490,2001.

[9] Lambert, J.-C., et al., A climatology of NOZ profile for improved air massfactors for ground-based vertical column measurements, Proc, 5‘h European

workshop on stratospheric ozone, Saint-Jean-de-Luz, France, 27 Sept -1 Ott1999.

[10] Leue, C., Wenig, M., Wagner, T., Klimm, 0,, Platt, U,, & Jahne, B., Quanti-tative analysis of NOZ emissions from Global Ozone Monitoring Experiment

satellite image sequences, J. Geophys.Res., 106, 5493-5505, 2001.[11] Martin, ”R,V,, et al., An improved retrieval of tropospheric nitrogen dioxide

from GOME, J! Geophys,Res., submitted 2002,[12] Richter, A,, & Burrows, J.P., Tropospheric NOZ from GOME measurements,

accepted for publication in Adv. Space Res.[13] Valks, P. J. M., Piters, A. J. M., Lambert, J, C,, and Zehner, C, & Kelder, H.,

A fast delivery system for the retrieval of near-real time ozone columns fromGOME data, accepted for publication in International Journal of RemoteSensing, 2002.

[14] Velders, G. J,M,, et al., Global tropospheric NOZ column distributions: Com-paring 3-D model calculations with GOME measurements, J Geophys.Res.,106, 12643-12660, 2001,


Documents

N02 and ozone observations from space and the prospect for ...At emission areas the N02 concentration will peak at the surface, while downstream of such areas the pollution plume will