Applications of IASI on MetOp-A : first results and illustration of potential use for meteorology, climate monitoring and atmospheric chemistry

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1 Applications of IASI on MetOp-A : first results and illustration of potential use for meteorology, climate monitoring and atmospheric chemistry Thierry Phulpin* a, Denis Blumstein a, Florent Prel a, Bernard Tournier b, Pascal Prunet b and Peter Schlüssel c a Centre National d Etudes Spatiales, 18 avenue E. Belin, Toulouse, France; b Noveltis, parc technologique du canal, Ramonville, France ; a EUMETSAT, am Kavalleriesand 31, Darmstadt, Germany ABSTRACT IASI was successfully launched on MetOP A on 19 october After the in-orbit commissioning, the performances of IASI were evaluated during the cal/val of level 1. Key parameters of instrument and on ground processing have been fixed for optimal performance and best quality data delivery. The first spectra and images of level 1 products show all the potential of IASI data for expected applications. Some illustrations are given here with maps of pseudo channels sensitive to trace gases, atmospheric profiles or maps of surface temperature qualitatively compared to maps from models. Level 2 processing to get these parameters has been implemented at Eumetsat and some products are currently under validation. The quality of IASI data paves the way to additional very promising products. A thorough analysis of cloud free spectra has been performed to extract the small signature of minor species like CFCs and HNO 3. Nevertheless, the main limitation of IASI data remains clouds. It is showed here with the cluster analysis of AVHRR data registered in the IASI pixels and delivered as level 1 products that only a few cloud free pixels can used for full retrieval. A method making use of the cluster information has been developed. It permits to strongly increase the statistics where clear column profiles or columns above clouds can be retrieved. This scheme will be applied to the retrieval of the CO 2 where large data set are needed to extract information from the spectra.. Keywords: IASI, Trace gases, cloud cover, AVHRR 1. INTRODUCTION The IASI instrument, embarked on MetOp-A, the first European polar meteorological satellite, was launched on October 19, 2006 on a SOYUZ rocket from Ba ikonur, Kazakhstan. The MetOp-A was placed on a sun-synchronous polar orbit at 820 km with the MLS time of 21:30 at ascending node. This satellite is the first of a series of 3 launched every 5 years, ensuring a continuity of data for a planned period of 15 years. IASI is a key element among the 12 instruments on-board (Klaes et al, 2007), the first of a new generation highly accurate infrared atmospheric sounder. It was designed by the Centre National d Etudes Spatiales (CNES), developed by CNES and Eumetsat and manufactured by ThalesAleniaSpace. According to the cooperative agreement between CNES and Eumetsat, CNES was also responsible of the development of Level 1 processing and the System In-Orbit Verification, the Calibration/Validation of the instrument during the commissioning phase. A first orbit was distributed to selected scientists in February. The data were also forwarded to the teams contributing to the cal/val, especially during the JAIVEX (Huang et al, 2007). The first data were delivered in a trial operational mode to some of the Numerical weather Prediction Centres from February 28. Some first results were already showed. This paper aims at illustrating the potential application of IASI. It also stresses the impact of the clouds and proposes some means to screen the clouds and show global products. A method to retrieve products in some given cloudy conditions is also proposed.

2 Fig. 1. Soyuz on the launch pad just before the launch of Metop -A on 19 October THE IASI INSTRUMENT IASI is a Michelson interferometer with a maximum Optical Path Difference (MOPD) of ± 1 cm (Ref). The spectra are acquired in 3 bands: cm -1, cm -1, cm -1. The IASI swath is about 2200 km, ensuring 99% global coverage twice a day. This swath is obtained thanks to a step by step scanning mirror covering ± range in 30 steps, each step every 3.3 (normal mode). At each step, the field of regard (FOR) includes 2 x 2 IFOV of 1.25 (12 km at nadir) positioned on lines and columns located at? degrees, leading to an horizontal sampling between 18 and 22 km at nadir (Figure 2a). The optical core of the instrument is cooled down to 91.3 K thanks to a 3-stage passive radiator. Data are calibrated on-board thanks to one blackbody and one space views every scan line. Note that for calibration purpose the scan can be stopped on request of the operator on a given scan position (e.g. at nadir) resulting in a transect profile with a very high oversampling (every 1.3 km). This is the external calibration mode (Figure 2b). Figure 2a : Geometry of IASI in normal mode: as the satellite moves upward, a scan line is made of 30 Fields of Regard (50 km at nadir), each including a dice of 4 IFOVs of 12 km diameter (at nadir). After 8 seconds and views of blackbody and cold space, a next scan line is observed. Figure 2b : External Calibration mode. The scan mirror is blocked in a fix position (e.g at nadir) allowing a high oversampling spectra in this direction An Integrated imager (IIS) is embedded in the focal plane of the interferometer. At each of the 30 scan positions, a 1km resolution image in the µm band is measured on its 64*64 pixels matrix of detectors. This imager has been designed to coregister AVHRR images with IASI and analyze the various targets contributing to the spectra measured by IASI at its resolution (Figure 3).

3 Figure 3 : Coregistered AVHRR cloud mask (left) and IASI data (channel at 925 cm -1, right). Example of 3 successive acquisitions over Western Europe (courtesy CMS Lannion) 3. CALIBRATION AND TESTS The IASI level 1 Cal/ Val was performed by the Technical expertise Centre at CNES. It aimed at validating the instrument properties with respect to the User requirements and performances measured on ground. The goal was also to optimize the instrument configurable parameters and to check that the level 1 data processing provides very accurate spectra at the different levels. This phase took place from December 20 after the first decontamination of the instrument. It was composed of 3 phases: Phase A (gross calibration and characterization) until 24 March, phase B until 17 July and Phase C (consolidation) from July All the results are presented in Blumstein et al (2007). The most remarkable results are the good radiometric performances: NeDT similar to the one measured on the ground, and very good absolule calibration. The very high spectral accuracy is also noticeable. 4. THE IASI LEVEL 1 PRODUCTS The IASI level 1 products are: - Level 1a products which are unapodised calibrated and geolocated spectra with corresponding IIS images. - Level 1b which are Level 1b after spectral resampling. - Level 1c: which are Level1b after apodis ation to obtain a nominal Instrument Response Spectral Function with 0.5 FWHM. The data are sampled every 0.25 cm-1. The results of analysis of AVHRR radiance over the IASI IFOV are appended. The data processing chain was developed under CNES responsibility. It is implemented at the Core Ground system at Eumetsat where data are operationally processed, archived and distributed. The level 1c are disseminated through Eumetcast (Klaes et Schmetz, 2007) to the NWP centres. A number of 320 channels is also now distributed via GTS. The data are also available at U-Marf, archiving facility managed by Eumetsat. A version of the Level1 software has also been developed to be integrated in the AAPP for local acquisition. If some NWP centres and selected scientists could receive some data as soon as from 13 February, the IASI level 1c have been distributed through Eumetcast and the U-Marf from 24 may They are now also available on the GTS. The Level 2 products are listed in Table 1. The Level 2 processing has been developed by Eumetsat based upon scientific algorithms studied by the IASI Science Sounding Working Group during the preparatory programme. They will be

4 archived and distributed by Eumetsat. The first products to be distributed will be the atmospheric profiles as soon as they are validated. GEOPHYSICAL VARIABLES ACCURACY VERTICAL RESOLUTION HORIZONTAL SAMPLING Temperature Profile 1K (cloudfree and low clouds) 1 km 25 km (cloudfree) Humidity Profile 10 % (cloudfree and low 1-2 km (troposphere) 25 km (cloudfree) clouds) (cloudfree) Ozone total amount Better than 5% per cloudfree N/A 25 km (cloudfree) pixel Ozone Vertical distribution 20% 0-6km 25 km 9% 8%. per cloudfree pixel 0-12 km 0-16 km Fractional cloud cover 5 to 10% Cloud top temperature 1 to 2 K (thick clouds) Cloud top height m/50-100m (PBL) 50 (100% cover) Or pressure (hpa) Cloud liquid water/ice path mm CO Total content CH 4 Total content N 2 O Total content 10 %/pixel 5-10%/pixel 5-10% N/A CO 2 2% N/A SO 2 (volcanic eruption)? HNO3? N/A CFC 12 10% N/A CFC 11, HCFC 22 20% N/A 25 km 25 km 100 km 25 km 100 km 100 km 100 km Sea Surface Temperature <0.5 K (cloudfree) 25 km Land Surface Temperature 1K (cloudfree) 25 km Land Surface Emissivy 0.5% (window) 1% (souding ch.) 25 km Table 1 : Level 2 products expected from IASI as established by the ISSWG 5. ILLUSTRATION OF IASI CAPABILITIES The figure 5 displays an example of a typical IASI spectrum compared to an AIRS spectrum. The most noticeable differences are: - the continuity of the IASI spectrum from 645 cm -1 to 2760 cm -1 (covering the CH 4 band); - its higher spectral resolution at higher wavenumbers allowing to clearly distinguish the CO and N 2 O lines; - There is no pops-up - The higher noise in the band 3 which makes individual spectral samples generally difficult to be used.

5 Figure 5: IASI (in blue) and AIRS spectra (in red) near the orbit crossing point (19 April 2007, S ). Coincident spectra are searched such as the time difference is lower than 5 seconds and the IASI pixel center is less than 3 km from the AIRS pixel. (Blumstein et al, 2007) On the figure 6 some spectra measured near the South pole have been averaged in region of about km by km. It turns out that in this relatively dry and cold region, (see spectra in the cm-1 H 2 O band, Figure 6a), the radiometric noise will mask the bands of minor trace gases like CFC 11, CFC 12 or HNO 3. Averaging the spectra allows us to reduce the noise and the fluctuations of water vapor and temperature profiles. The mean spectra are remarkably good showing very clearly the CO 2 laser band near 980 cm-1 and the minor trace gases bands. As a first trial a simulated spectrum was fitted on the measurements with a pretty good agreement. Note that as CFCs are supposed to be well mixed and distributed over the globe, they can be measured in region. It would be more accurate where surface temperature is high as there is more signal. However the water vapor lines would then mask the CFC absorption band. A fine measurement would take advantage of averaging over the globe after either inverting atmospheric profiles or selecting very dry profiles. The External calibration mode would also be a very appropriate means to average spectra in very similar atmospheric conditions.

6 Figure 6 : Detection of minor trace gases. Figure 6a shows typical spectra in the atmospheric window over a region near the south pole. Noise is strongly and water vapour lines (even if not too strong) mask the absorption bands. On figure 6 b a mean of 540 spectra obtained in external calibration mode (over 900 km). Figure 6c Evidence of HCHC-22, HNO3, CFC-11, and CFC 12 on the spectra

7 Figure 7 : Illustration of typical IASI spectra along a selected orbit. The mean brightness temperature over cm-1 are displayed only for one of the 4 FOVS at -30, 0 and 30 with the color scale given beyond. On the left lower part, the

8 band in greyscale is the IIS image. Spectra are extracted for the numbered spots indicated on the 2 images. 1 is for a very hot IFOV over Ouzbekistan, 2 is a very singular spectrum over Iran in a desert area, 3 is a large cirrus cloud over Indian ocean, 4 is a cold cloud over, 5 is a thick and high cold cloud over Antarctica, 6 is clouds over equatorial Pacific ocean, 7 is a very flat spectrum where column over the cloud. On the figure 7 we show some peculiar spectra measured along a given orbit. Spectra have been extracted only for three angles -30, 0+, 30. The spectrum measured over the South Arabia shows the Restrahlen emissivity effect due toe the silicate enlarged in Figure 8. Figure 8 : Restrahlen effect over a desert area in Iran. The sunglint effect from 2500 to 2760 cm-1 can be so high that radiance is doubled, inferring a strong increase of the signal to noise ratio in this band. This can be used to retrieve the CH 4 column, the absorption lines of which being then clearly evidenced with respect to radiometric noise (Figure 9). Figure 9 : Retrieval of CH 4.column in sunglint areas These examples show that beyond the level 2 products studied by the ISSWG, more products could be derived from IASI and lead to robust applications, not set as a first priority for IASI. A list of pseudo channels have been defined for different products (Table 2). A pseudo channel is there a linear combinations of brightness temperatures measured in channels where the sensitivity to a single component is the highest. It can be a single channel as well, but averaging permits to reduce the effect of radiometric noise. In some cases, we subtracted the channel exhibiting the same sensitivity in temperature or a channel very close in a window. Products Pseudo channels Criteria of selection Temperature profile

9 - 0 to 50 hpa - 50 to 200 h Pa to 500 hpa to 750 hpa to 900 hpa Humidity profile < 400 hpa hpa hpa Carbon monoxide Ozone Methane Surface temperature to , , , ±1, 1332± , , B3 : ; ;2627,2632, , ;2749 B1 : 23 spectra samples from to Table 2 : Pseudo channels for IASI products. Highest jacobien, no water line Id. Id. Id. Id Highest jacobian for various atmsophere Id Id Highest jacobian low for H2O Highest jacobian low for H2O Absorbing band in solar spectrum Transmittance > DT<0.35 K Highest transmittance and lowest atmospheric effect A full day with 14 orbits has been processed and image of pseudo channels are illustrated in figure. The cloud cover is very high and screens the geographic distribution structures which are expected. A cloud mask has to be defined and superimposed to those images. 6. CLOUD CONTAMINATION The IASI level 2 processing includes some different algorithms either based on IASI stand alone data or other instruments or ancillary data to establish a cloud mask or even characterize the cloud (Schlüssel et al, 2004). Before such a mask is available at level 2, a simple method has to be developed in order to interpret with a good confidence the pseudo channel global maps studied in this paper. The method used here is a threshold method applied to IASI spectra. It makes use of the cloud spectral properties illustrated on figure 7 where the spectra of several clouds systems detected on the IIS images were displayed. The main characteristics are the following : - for most of clouds, the brightness temperature is very cold, giving spectra colder in all bands but the strong CO 2 or H 2 O absorption bands; - for high clouds, water vapour content above, being small, the absorption lines of weak lines near 790 cm-1 are not as deep as in clear situations; the presence of cirrus is detected as the ice emissivity increases with the wavenumber from 770 cm -1 to 1000 cm -1. In some cases the spectra are inverted with warmer temperature in the absorption bands (emission by stratospheric layers warmer than the clouds below). Looking at small clouds detected on AVHRR or IIS images show that they are difficult to discriminate through singular spectral signatures. As clouds generally exhibit brightness temperature in atmospheric windows T window lower than the surface, many clouds will be detected by a single comparison with the surface temperature. This could be derived from NWP analyses. In that case, a difference of 15 K (according to Clerbaux, personal communication) is considered to take into account the atmospheric absorption depending mostly on the water vapour content, the viewing angle and the surface emissivity. Another method is to consider that surface temperature distribution is mostly zonal and use the highest T window (taken typically around 965 cm -1 ) in a band of scan lines as a reference cloud free temperature T clear. Then any IFOV with T window 10 K lower than T clear is considered as cloud contaminated. This technique (in that case T clear is computed for areas of 3000 * 3000 km) has been used and applied on a full orbit taken as a good statistical sample. To screen out the thin cirrus, it has be complemented by a threshold on the slope in

10 the cm-1 window region. To delineate small clouds a test on heterogeneity is applied. The variance of the IIS inside the IFIV is computed. As soon as the standard deviation is higher than 1 k, the IFOV is declared cloudy. This method was then applied on a series of 8 successive orbits giving a full coverage of the Earth on 15 July This is applied to 2 pseudo channels. The pseudo channel for the Surface temperature and the one for. The map of temperature is compared to the one given produced by Mercator (analysis of 11 July 2007) (Figure 10). The Pseudo channels for surface temperature have been selected as those in the 2700 cm-1 atmospheric window with no interference absorption lines of CO 2 or H 2 O lines and an atmospheric transmittance higher than The brightness temperature is thus supposed to be within 0.35 K of the actual SST. The measurements are only taken at night. Despite the radiometric noise in this band, it is strongly reduced by averaging over 30 spectral samples. Figure 10 : Surface temperature pseudo channel for 8 orbits 15 july 2007 It is seen that the cloud cover is so high that it reduces drastically the time and spatial sampling of data. If this can be accommodated when data are assimilated in a model where the background and the physics can compensate the holes in the observations, some other products would need a higher spatial sampling. That is the case for greenhouse gases monitoring like CO2 where more observations are needed to guide the models. A method has been developed to better use IASI information in case of cloudy scenes or more generally inhomogeneous scenes. This is based upon a 1d-var scheme allowing to retrieve the characteristic of 4 surfaces, supposed to exhibit the same spectra in a dice of 4 IFOVs (Prunet, 2007). The AVHRR cluster analysis in the IASI FOVS (Cayla, 2000) results in 7 classes. Each of them is characterized by its position in the IFOV, a number of pixels, the mean and standard deviation values for the 5 AVHRR channels. Among those 7 classes, one gathers all unclassified pixels. The clusters characteristics are available in the IASI level 1c format. At a first stage of the method, the classes are merged according to their main features to get only 4 classes. Then knowing the population of the 4 classes for the set of 4 pixels, the equation system is inverted where it is possible, giving the spectra for each of the 4 classes. Afterwards a correction to remove self apodization of the spectra due to the presence of heterogeneities in off-axis IFOVs is applied. The method has been applied on 10 successive orbits acquired on 15 and 16 January The number of cloudfree IASI IFOVS over the Ocean is very low: 3% if no tolerance, 5% if a contamination of 10% cloudy pixels is accepted. The number of partly cloudy FORs over sea is about 25 % and in 16 % of situations cloud clearing permits to get spectra with a rms of 0.5 K in the same channels as AVHRR. Note that for better results of the method, all the FORs with a class of unclassified pixels (80%) were discarded. This method allows us also to identify FORs where sea surface and a single low cloud is present. In such situations the two spectra can be used to retrieve a atmospheric component in the layer near the surface. This is expected to be used in the next study to retrieve CO2 emission areas. 7. CONCLUSIONS The IASI data are extremely good and the feedback from the ECMWF on the first impact of IASI on the weather forecast is very positive. But besides this first IASI objective, the good data quality is such that many other products can be expected. It has been showed that trace gases like the CFC can be quantified, that surface could be characterized by their emissivity signature. IASI is also promising for the methane or to improve the SST measurements. However at IASI spatial resolution, cloud cover makes the usable data quite sparse. A method has been proposed to increase the density of IASI data. It could be applied for products where averaging on time series is necessary like CO2 retrieval. REFERENCES 1. D. Klaes and J. Schmetz, The EUMETSAT polar system status and first results, SPIE conference, Vo 6684, San Diego, 2007.

11 2. D. Blumstein, B. Tournier, F. R Cayla, T. Phulpin, R. Fjo rtoft, C. Buil, and G. Ponce, "In-flight performance of the infrared atmospheric sounding interferometer (IASI) on METOP-A, SPIE Conference, Vol 6684, San Diego, P. Schlüssel, T. H. Hultberg, P.L. Phillips, T. August, X.. Calbet, The operational IASI Level 2 processor, Advances in Space Research 36 (2005) , P. Prunet,, IWGGMS, Paris, June F.R Cayla, AVHRRradiance analysis inside the IASI FOVs,