VALIDATION OF MIPAS WATER VAPOR PRODUCTS BY GROUND BASED MEASUREMENTS

Transcription

1 VALIDATION OF MIPAS WATER VAPOR PRODUCTS BY GROUND BASED MEASUREMENTS Gelsomina Pappalardo (1), Tiziana Colavitto (2), Fernando Congeduti (2), Vincenzo Cuomo (1), Beat Deuber (3), Niklaus Kämpfer (3), Marco Iarlori (4), Lucia Mona (1), Vincenzo Rizi (4) (1) Istituto di Metodologie per l Analisi Ambientale IMAA CNR,C.da S.Loja, Tito Scalo (Pz), Italy, I (2) Isituto di Scienze dell Atmosfera e del Clima ISAC-CNR, via del Fosso delcavaliere 100, Roma, Italy, I (3) Institute of Applied Physics, University of Bern, Swirtzerland (4) Dipartimento di Fisica, Università degli Studi- L Aquila, via Vetoio, loc. Coppito, L Aquila, Italy, I ABSTRACT Results of the ground based validation of MIPAS level 2 products, processed with software version 4.61, are reported. Data relative to the whole altitude range investigated by MIPAS, 60-5 km, have been validated by means of a microwave radiometer, for the middle atmospheric range, and by means of three radiosounding and Raman lidar systems for what concerns the upper troposphere and lower stratosphere (UTLS). Over 195 cases, a mean overestimation of 7-15% has been observed in the altitude range km. On the contrary, both lidar and radiosonde indicate an underestimation of about g/kg in MIPAS data in the altitude range of km. However, for comparison in UTLS only few data are until now available, and a larger amount of reprocessed MIPAS data are needed to draw more quantitative conclusion in this atmospheric region. 1. INTRODUCTION In March 2002, ESA launched the ENVISAT satellite, an advanced polar-orbiting Earth observation satellite that provides measurements for studying and monitoring the Earth and its environment. Ten instruments of advanced technological level perform measurements of land, atmosphere, ocean and ice, allowing to better understand climatic processes and to improve climate models. MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), one of the three ENVISAT atmospheric instruments, is a Fourier transform spectrometer that operates in the near to mid infrared for the measurement of high-resolution gaseous emission spectra at the Earth's limb. MIPAS provides vertical profiles of pressure, temperature and atmospheric constituents, as CH 4, CO 2, O 3, and H 2 O with a vertical resolution of 3-4 km, extended down to 5 km. After the first validation workshop, held in Frascati in December 2002, a big effort has been spent in the optimization of the retrieval algorithm. The validation dataset for the second validation workshop consists of MIPAS level 2 products processed with software version 4.61, released in March Here, we present results of the validation of water vapor MIPAS level 2 products processed with software version Only a subset of the dataset requested by the validation groups is available up to now, including many data of the 2002, some data after 24 th February 2004 and a little amount of data acquired in the This reprocessed dataset is sufficient for drawing first results of the validation campaign. A precision of 5% and an accuracy of 5-10% were estimated before launch for water vapor products, but these estimations, as well as the profiles, have to be validated by means of ground based validation campaigns. In order to compare MIPAS water vapor profiles with measurements obtained from different instruments, the differences of the observing systems, in particular the different vertical resolution, have to be taken into account. For this purpose, Averaging Kernels Matrices of MIPAS for both Near Real Time and Off-Line products have been developed by IFAC-CNR [1, 2]. These matrices allow to reduce MIPAS profiles to a vertical resolution of 1km. For water vapor profiles, average kernel matrix applies to retrieval altitudes between 60 and 12 km, while for data at 9 and 6 km the kernel is not available because of the high instability of the retrieval at these altitudes. For a correct comparison, all error sources have to be considered, so in addition to the error reported in the level 2 products distributed by ESA, also the systematic errors that affect the water vapor MIPAS profiles have been taken into account using the error analysis performed by the Oxford University for both near real time and off-line products (see For the validation of the MIPAS water vapor profiles, we compare level 2 products with coincident measurements by different instruments: a radiometer for the middle atmosphere range, radiosounding and Raman lidar systems for what concerns the upper troposphere and lower stratosphere (UTLS). Proceedings of the Second Workshop on the Atmospheric Chemistry Validation of ENVISAT (ACVE-2) ESA-ESRIN, Frascati, Italy, 3-7 May 2004 (ESA SP-562, August 2004) EMI02GP

2 2. THE MIDDLE ATMOSPHERE RANGE The water vapor distribution in the middle atmosphere can be explained as a balance between dry air coming from the tropical tropopause, the methane oxidation in the upper stratosphere that acts as a source of water vapor and a transport to the troposphere via the extratropical tropopause. There are only few studies that analyzed long-term changes of stratospheric water vapor, but they agree indicating that water vapor increases at a rate of about 1% per year in the stratospheric altitude range. At the present time, there is a poor knowledge of the long-term dynamical behavior of the water vapor in the stratosphere and on the exchange of water vapor between troposphere and stratosphere. MIPAS water vapor measurements, covering part of the mesosphere and the whole stratosphere, with global coverage, represent a big contribution for monitoring long-term changes. Among the remote sensing techniques for H 2 O measurements, microwave spectrometry is one of those techniques that allow to investigate the middle atmosphere with a good accuracy [3], so it is a reliable instrument for the validation of MIPAS data in this altitude range. The ground-based radiometer MIAWARA (Middle Atmospheric Water Vapor Radiometer) measures the GHz emission line of the rotational transition of water vapor. Using inverse optimal estimation technique the stratospheric and mesospheric water vapor profile in the range of km can be retrieved with this instrument. A detailed description of the instrument and its technique can be found in [4] and [5]. In 2003 MIAWARA was in operation at Bern, Switzerland (46.95 N, 7.45 E, 550 m above sea level) for almost the whole year. From February to April 2004 the instrument was operated at Sodankylä, Finland (67.37 N, E, 179 m above sea level), where it took part in the LAUTLOS validation campaign. To have a reasonable number of intercomparisons all MIPAS profiles at a distance +/- 5 degrees in latitude and +/- 5 degrees in longitude were considered for the intercomparison with the MIAWARA instrument. For the days of operation in 2003 at Bern, 195 water vapor MIPAS profiles on 65 different days were compared with 65 MIAWARA 24-hour average profiles over Bern. Fig. 1: Sample MIAWARA (blue solid) with measurement error (blue dashed) and MIPAS (convoluted: red solid, original grid: red dashed) on February 17, The MIPAS retrieval was located at N E.

3 Fig. 2: Mean Difference of all coincident MIAWARA and MIPAS Profiles in 2003 (+/-5 lat. +/-5 lon.). The dashed lines represent twice the standard deviation of the mean value (2σ). To achieve an identical resolution of the profiles measured by the different techniques and to account for the a priori profile contribution in the MIAWARA retrieval, the MIPAS profiles were convoluted with the averaging kernel matrix and the a priori profile of the MIAWARA retrieval. In Fig. 1 a sample comparison for February 17 th, 2003 is shown: the difference for this case is better than 5% for all altitudes with a slight negative bias of the MIAWARA profile. In Fig. 2 the mean difference (MIAWARA MIPAS)/MIPAS for all coincident profiles in 2003 is shown. The dashed lines represent the 2σ of the mean value. This mean difference shows a negative bias for the MIAWARA instrument in respect to the MIPAS profiles in the range of -7 % (at 28 km) to -15% (at 55 km). For this mean difference all 195 measurements of MIPAS, as available on the MIPAS data server, were taken into account and no further quality check was performed. For some cases the individual profiles show differences in the range up to 30-40%. An additional intercomparison could be performed using the dataset measured by MIAWARA during the LAUTLOS campaign in early 2004, where, besides the MIAWARA measurements, additional data from aircraft, stratospheric balloon soundings and satellites are available. 3. THE UTLS REGION The water vapor content in the upper troposphere and lower stratosphere (UTLS) has a main role in the radiation balance and in the UTLS chemistry. In fact, it is well known that water vapor is an high efficient green-house gas and recent studies have shown that small changes in the UTLS water vapor concentration can significantly alter Earth s radiation budget [6, 7]. This means that an high accuracy is needed for water vapor measurements in this atmospheric range, in particular it was estimated that the accuracy of these measurements must be in the range of 3-10%, otherwise the error committed in the radiative forcing calculation would be comparable with the effect due to doubling the CO 2 concentration [8]. Large and small scale distribution of the UTLS water vapor concentration as well as its seasonal, annual and longer time scale changes are poorly known. The ENVISAT space mission and the MIPAS capability to retrieve water vapor vertical profiles down to 5 km of altitude can be a powerful tool for a more in-depth characterization of UTLS water vapor. To validate these data, radiosounding and Raman lidar systems have been used in three Italian stations involved in the GMBCD (Ground Based Measurements and Campaign Dataset)

4 for the ENVISAT products validation. A new radiosonde sensor and/or a correction algorithm [9] have been used in order to avoid problems of poor quality data at cold temperature (under 60 C). The Raman lidar technique has the capability to retrieve water vapor mixing ratio, in a relatively free of error way, with high resolution both in time and space from the planetary boundary layer up to the tropopause [7, 8]. 3.1 University of L Aquila contribution L Aquila lidar system (Italy, N, E, site elevation 683m above sea level) is based on an XeF excimer laser as source of the light pulses. The backscattered light is collected by a zenith pointing telescope, spectrally separated by optical systems and transported by an optical fiber to a 4-channels receiver. The relevant characteristics of L Aquila lidar system are reported in Table 1. LASER SOURCE: XeF excimer (Lambda Physik) Wavelength and pulse energy 351 nm E = mj Pulse repetition rate 30 Hz Beam divergence ~0.4 mrad Pulse duration 20 ns RECEIVER: Parabolic mirror Mirror diameter 0.2 m Central obscuration diameter 0.05 m Focal length 0.6 m SPECTRAL SELECTION: Interference filter Wavelengths 351, 382, 393, 403 nm Bandwidth 6, 6, 4, 6 nm Out of band rejection 10-12, 10-16, 10-18, Transmission efficiency 62%, 54%, 73%, 52% DETECTORS: Photomultipliers THORN EMI 9214QB ACQUISITION: Photon counting Minimum dwell time 500 ns Bandwidth 150 MHz Tab. 1: main characteristics of the lidar system of the Università degli Studi- L Aquila. The detector unit has been optimized in order to investigate a range of altitudes from ground up to 7000 m. To do so, the optimization for the detection of weak Raman backscatterings by N 2, H 2 O vapor and cloud droplet liquid water, and the suppression of background light and of cross-talking between the different channels are necessary. These conditions impose restrictions on the choice of the receiving optics (telescope) and on the design of the dichroic beam splitters, interference and notch filters (which provide an additional suppression of the strong elastically backscattered light in Raman channels) to be used in the detector unit. The light is detected by high gain photomultipliers, in each channel the read-out system is made up of a fast preamplifier, a pulse discriminator and an high speed multichannel scaler, finally the data are stored and displayed in a personal computer. This lidar system is primarily devoted to retrieve aerosols optical parameters in the planetary boundary layer, so although L Aquila lidar system is capable to extract water vapor profile, in normal operation the maximum useful altitude for this retrieve is about 5 km [12, 13]. Routine lidar measurements of tropospheric aerosol, water vapor and liquid water are performed twice a week, in coincidence with radiosounding measurements of pressure, temperature and relative humidity. As part of the ground based validation group involved in the water vapor MIPAS validation, L Aquila main contribution comes from balloon borne radiosoundings. Only overpasses with a maximum distance of 500 km from University of L Aquila has been considered for the comparison. Starting from February 2003 until May 2004, there are 21 cases of coincidence between L Aquila routine measurements and MIPAS overpasses (see Table 2), unfortunately at the moment of the second validation workshop only 1 of these MIPAS data was reprocessed. Date Time Orbit 06/feb/ : /feb/ : /feb/ : /mar/ : /mar/ : /apr/ : /mag/ : /mag/ : /lug/ : /lug/ : /set/ : /nov/ : /dic/ : /dic/ : /dic/ : /gen/ : /mar/ : /mar/ : /mar/ : /mar/ : /apr/ : Tab.2: list of the coincidence between radiosounding measurements in L Aquila and MIPAS overpasses: the date and time of MIPAS overpasses are reported together with the number of absolute orbit.

5 In Fig. 3, we report an example of intercomparison between L Aquila radiosonde water vapor profile and the MIPAS one for the 17 th March The comparison is possible for the four latest points of the MIPAS profile, where radiosonde data are less reliable. The MIPAS profile seems to follow the vertical profile of water vapor observed by radiosonde, but an underestimation of about 50% has been found at altitude higher than 11 km. Altitude above sea level (km) E-4 1E Fig. 3: example of intercomparison between radiosonde and MIPAS water vapor profiles for the 17 th March ISAC-CNR contribution Radiosonde Water vapor mixing ratio (g/kg) The system used in Rome Tor Vergata (41.83 N, E, 115m a.s.l.) for the validation of the MIPAS water vapor measurements is a Rayleigh/Mie/Raman lidar. The light source is a Nd:YAG pulsed laser which emits two beams at 532 and 355 nm with 150 and 320 mj pulse energies, respectively. In order to cover an operating range from the planetary boundary layer through the mesopause, the lidar system is based on a multiple-telescope configuration [14]. In the final configuration of the lidar three distinct receivers will collect the backscattered radiation by dividing the altitude range into smaller and partially overlapping intervals. The first channel is an array of nine Newtonian telescopes, it is used to detect the weak signal backscattered from km. The second channel is a single Newtonian telescope of 30 cm diameter with a 2-45 km sounding range. Finally for the third channel, a single mirror of 15 cm diameter is used with a km sounding range. Actually, only one of the telescopes of the array was operating during the validation campaign. The light incident on each telescope is focused onto an optical system, where the visible (532 nm) and ultraviolet (355 nm) components are split. In each UV channel there is a second optical system which separates the N2 Raman signal (386.7 nm) and the water vapor Raman signal (407.5 nm). Optical fibers carry the light to the photomultipliers. At the end of the optical fibers for the high altitude sounding channels, three choppers prevent the light scattered by the lower layers reaching the detectors, to avoid blinding of the photomultipliers by too intense signal. All choppers are synchronized with each other and with the laser pulse with accuracy less than 10µs. The signal from the photomultipliers is amplified and measured through photon counting and AD conversion techniques. Finally, the data are transferred to a PC where they are stored. The characteristics of the water vapor Raman channels are shown in Tab.3. LASER SOURCE: Nd:YAG laser (Continuum) Wavelength and pulse energy 355 nm E MAX = 320 mj Maximum pulse repetition rate 10 Hz Beam divergence 0.2 mrad Pulse duration 7 ns RECEIVER: Newtonian telescope Collector 1 Diameter 0.3 m Field of view 0.9 mrad Collector 2 Diameter 0.5 m Field of view 0.6 mrad SPECTRAL SELECTION: Interference filter Wavelengths 387, 407 nm Bandwidth 5, 4 nm Out of band rejection 10-9, Transmission efficiency 65%, 50% DETECTORS: Photomultipliers THORN EMI 9954B 532 nm THORN EMI 9214QB 387 nm, 407 nm ACQUISITION: Photon counting Minimum dwell time 500 ns Bandwidth 200 MHz Tab. 3: characteristics of the ISAC-CNR Raman lidar for water vapor profiles. In the frame of the validation activity for water vapor MIPAS data with Raman lidar of Rome, all the observations are complemented with radiosonde profiles. The used radiosonde is a RS90 Vaisala PTU model and the data have been supplied by the National Meteorological Service of the Military Aeronautics (Pratica di Mare, about 25 km South-West of Rome). The measurement campaign for the validation of ENVISAT products started on August 2002 and it

6 continued until March The measurements in coincidence with ENVISAT overpasses are listed in Tab.4. The lidar measurements performed at ISAC- CNR in coincidence with ENVISAT overpasses are 20 but only 4 comparisons with MIPAS 4.61 processor are possible, because the reprocessing of the MIPAS data for the year 2003 and for the beginning of the 2004 is still in progress. Day Time Orbit v /08/ : X 10/11/ : X 09/07/ : /07/ : /07/ : /07/ : /07/ : /07/ : /08/ : /09/ : /09/ : /09/ : /10/ : /10/ : /11/ : /12/ : /01/ : /01/ : /03/ : X 15/03/ : X Tab. 4: list of ISAC-CNR lidar measurement in coincident with MIPAS overpasses. Two examples of comparison among water vapor profiles from MIPAS, Raman lidar and radiosonde are presented in Fig.4-5. On August 2, 2002 lidar data are represented with an integration time of 80 min. and a vertical resolution of 75 m up to 6 km and 525m above that altitude. MIPAS profile has a space distance of 537 km from the lidar station and a temporal distance of about 5h from the beginning of the lidar measurements. Lidar seems to be in a good agreement with radiosonde profile, but in this case a direct comparison with MIPAS is not possible because MIPAS vertical profile extends down to about 9 km while lidar vertical profile does not reach that altitude. On the other hand there is a good accordance between MIPAS and radiosonde profiles approximately in the range 9 12 km. On March 15, 2004 the lidar measurements are integrated over 60 minutes and they have the same vertical resolution of the lidar data measured on 2 August The temporal distance is about 90 minutes from the lidar measurements and the spatial distance from the ground station is 767 km. The comparison is possible only around one MIPAS experimental point at about 9 km height. Above that altitude the comparison is possible only between MIPAS and radiosonde profiles which seem to be different. Around 12 km MIPAS water vapor mixing ratio values are almost 10 times smaller than the ones measured by radiosonde. This should be attributed to loosing in accuracy of the MIPAS measurements in atmospheric layers with high water vapor gradient. Altitude above sea level (km) Lidar (04:39:00-06:05:15 UT) Radiosonde (00:00 UT) (23:25:24-23:26:35 UT) 0 1E Water vapor mixing ratio (g/kg) Fig. 4: intercomparison between MIPAS and co-located ISAC-CNR radiosonde and lidar data for 2 nd August Altitude above sea level (km) Lidar(20:42-21:55 UT) Radiosonde (18:00 UT) Radiosonde (23:00 UT) (21:57:25-21:58:36 UT) Rome, 2 August 2002 Rome,15 March E-4 1E Water vapor mixing ratio (g/kg) Fig. 5: intercomparison between MIPAS and co-located ISAC-CNR radiosonde and lidar data for 15 th March 2002.

7 0.1 H2 O (g kg-1 ) E-3 1E-4 1E-4 1E Radiosonde H2 O (g kg-1 ) Fig. 6: scatter plot of MIPAS versus ISAC-CNR radiosonde water vapor data. In order to have a quantitative estimate of the comparison, MIPAS-radiosonde comparisons for the month of March 2004 have been considered, as it is shown in Fig.6. For this plot, the radiosonde data have been averaged within altitude ranges corresponding to the MIPAS space resolution and the horizontal error bars represent the root mean square variation of the radiosonde profile inside each averaging range. Three days have been considered and 14 points, corresponding to the altitude range 9 km 21 km, have been compared. Although few days have been considered, a clear underestimation of MIPAS respect to radiosonde data is evident. The difference between the two considered datasets reaches in some cases one order of magnitude and has a mean value of g/kg, calculated as mean on the whole altitude range of MIPAS-radiosonde overlapping. In this validation work only 4 water vapor mixing ratio comparisons between lidar and MIPAS (4.61 processor version) have been possible, on one hand due to unavailability of the reprocessed MIPAS data for the year 2003 and on the other hand due to rainy weather and technical upgrade work of the lidar system during the year Even after recent reprocessing, the MIPAS profiles rarely extend below 9 km, therefore the comparison with lidar was often possible around one MIPAS experimental point and a quite good accordance seems to hold. Above 10 km height MIPAS profile seems to underestimate lidar water vapor mixing ratio and the radiosonde data confirms this underestimation. A more significant statistical analysis will be possible as soon as a larger MIPAS reprocessed dataset is available. 3.3 IMAA-CNR contribution The IMAA-CNR lidar system for vertical profiling of water vapor is able to determine the water vapor content starting from about 100 m up to 12 km above the lidar station, with high resolution both in time and space. Because of its capability to retrieve aerosol extinction and backscatter coefficient profiles, this system is an excellent instrument for studying water vapor dynamics in the PBL, for investigating correlations between humidity and aerosol optical properties [15, 16], and for improving the knowledge of the UTLS water vapor content and validating satellite data in this atmospheric region. This system is a Raman lidar system based on a Nd:YAG laser source with a maximum repetition rate of 100 Hz (typical operative configuration of 50 Hz). A third harmonic generator allows to obtain radiation at 355 nm with a maximum energy per pulse of 170 mj. The UV beam is transmitted into the atmosphere in a

8 coaxial mode. A telescope in Cassegrain configuration, with 0.5 m primary mirror, collects radiation backscattered by the atmosphere. A spectral separation into three channels is obtained by means of dichroic mirrors. Interferential filters are used to select elastically backscattered radiation, and Nitrogen and water vapor Raman signals, respectively at 355, 387 and nm. For each wavelength, a signal with a good dynamic range is obtained splitting the output of the interferential filter in two by means of beam splitters and detecting separately signals coming from low and high altitude range. Photomultiplier are used as detector and signals are acquired in photon counting by a Multi Channel Scaler (MCS). The main characteristic of IMAA-CNR system are reported in Tab. 5. LASER SOURCE: Nd:YAG laser (Coherent) Wavelength and pulse energy 355 nm E MAX = 170 mj Pulse repetition rate 50 Hz Beam divergence 0.4 mrad Pulse duration 3 4 ns RECEIVER: Cassegrain telescope Primary mirror diameter 0.5 m Combined focal length 5 m Night time Field of view Day time Field of view 1 mrad 0.6 mrad SPECTRAL SELECTION: Interference filter (Barr Associates) Wavelengths 355 nm, 387 nm, 407 nm Bandwidth night time operation Bandwidth daytime operation 1.0 nm 0.5 nm Out of band rejection 10-6, 10-8, Transmission efficiency 33%, 62%, 60% DETECTORS: Photomultipliers THORN EMI 9383 QB 355 nm THORN EMI 9202 QB 387 nm, 407 nm ACQUISITION: Photon counting EG&G Ortec MCS Minimum dwell time 100 ns Bandwidth 150 MHz PHILLIPS SCIENTIFIC fast discriminator Bandwidth 300 MHz Tab. 5: characteristics of the IMAA-CNR Raman lidar system for water vapor measurements. Raw lidar signals are acquired over 1 minute, corresponding to 3000 laser shots, and with a spatial resolution of 15 m. A nonstationary Wiener filter [17] is applied to the ratio of water vapor and Nitrogen Raman signals, quantity proportional to the water vapor content in the atmosphere. This filter allows to obtain a low relative error for the water vapor mixing ratio also in the upper troposphere. The system has been calibrated by means of an intensive measurements campaign of colocated and simultaneous Vaisala RS80-A radiosonde launches and water vapor Raman lidar measurements, in the period May-June 2002 [18]. All radiosonde data have been corrected for temperature dependence, chemical contamination, age of the radiosonde and ground check error [9]. Since July 2002, more than 60 radiosondes have been launched at IMAA-CNR allowing a long term calibration of the Raman lidar system and showing that the uncertainty on the calibration constant is lower 3%. The water vapor mixing ratio vertical profiles are typically obtained integrating signals over 10 minutes. In clear sky night time condition, water vapor profile typically covers an altitude range extended between 100 m above the lidar station up to the tropopause, with a final vertical resolution variable with the altitude between 15 m and about 700 m in the altitude range 90 m 10 km above lidar station. In the frame of the calibration/validation program of the ENVISAT atmospheric products, two measurements per week, in coincidence with satellite overpasses, were scheduled at IMAA-CNR for the first six months of satellite effectiveness (July-December 2002), while one measurement per week was scheduled for the following six months (January-June 2003) [19]. However, at IMAA-CNR water vapor measurements are still performed in a regular way and many data in coincidence of MIPAS overpasses have been collected also after the end of the validation period. For the comparison of MIPAS data with lidar and radiosonde profiles, a maximum distance of 1000 km has been considered. Only cases with a maximum temporal distance of 150 minutes between radiosonde launch and MIPAS overpasses have been considered, while water vapor lidar profiles have been obtained with a temporal integration window centered around the MIPAS overpass. Until 15 th April 2004, 73 lidar and 47 radiosonde measurements in coincidence with MIPAS overpasses have been collected. Until the same date, MIPAS water vapor profiles reprocessed with software version 4.61 were available only for 24 and 14 comparisons respectively with IMAA-CNR lidar and radiosonde profiles. More details about occurrences of measurements performed at IMAA-CNR in coincidence with MIPAS are reported in Tab. 6. Comparisons have been done in terms of water vapor mixing ratio, that is the direct product of Raman lidar while for MIPAS and radiosonde is obtained by water vapor products and simultaneous pressure and temperature profiles. In Fig. 7, a typical example of contemporary measurements performed by IMAA-CNR radiosonde and lidar, and MIPAS is reported. On 16 th October, 2002, as in most cases, the lowest point of the MIPAS profile is at about 9 km of altitude, so that only two points of the MIPAS data can be validated by means of the lidar measurements. In addition, the average kernel is not available for water vapor profile at altitude lower

9 than 12 km, thus no more than three values, typical two, for each MIPAS profile can be compared with lidar data. In this case, a good agreement between MIPAS and lidar data is observed, while radiosonde seems to underestimate the water vapor content. This underestimation can be related to two reasons: MIPAS retrieval is poor accurate at these altitude because of the sharp gradient in the water vapor profile at the tropopause, but, on the other hand, radiosonde data at these altitudes are not so reliable because of bad functioning of radiosonde sensor at low temperature. In Fig. 8, the only case of MIPAS profile extended down to 5 km and useful for validation with IMAA- CNR data is reported. The agreement among the profiles is quite good if the spatial atmospheric variability is taken into account. Day Lidar Sonde Time Orbit Day Lidar Sonde Time Orbit v v X X 21: X X 20: X 20: X X X 21: X 20: X 20: X 20: X 21: X X 21: X 20: X X 20: X X 21: X X X X 20: X X 21: X X X 20: X X 21: X 20: X X 20: X X 21: X X 21: X X 20: X X 20: X X 21: X X 20: X X 21: X X X 21: X X 20: X X 20: X 21: X X 20: X X 20: X X X 21: X X 20: X X 21: X X 20: X X X 21: X X X X X 21: X 21: X X X 21: X 21: X X 21: X 20: X 21: X 20: X X 21: X X 20: X X 21: X X 21: X X 21: X X 20: X 21: X 20: X X 20: X 20: X X 21: X 21: X X X 21: X 21: X 21: X X 21: X X 20: X 20: X X 21: X 9: X X 20: X X 21: X 21: X 20: X X 20: X X 21: X 21: X 21: X 21: X 20: X X 20: X X 21: X X X 21: X X 20: Tab. 6: complete list of IMAA-CNR measurements in coincidence with MIPAS overpasses. For each day, we report time of overpass and absolute orbit number, and we evidence with a cross if there are lidar and/or radiosounding measurements and if MIPAS level 2 products processed with software version 4.61 are available.

10 20 20 Altitude above sea level (km) Altitude above sea level (km) Lidar 20:23-20:33 UT 20:34 UT Radiosonde started at 20:17 UT 0 1E-4 1E Water vapor mixing ratio (g/kg) Lidar 21:22-21:32 UT 21:35 UT Radiosonde started at 21:18 UT 0 1E-4 1E Water vapor mixing ratio (g/kg) Fig. 7: intercomparison between MIPAS and co-located IMAA-CNR radiosonde and lidar data for 16 th October Fig. 8: intercomparison between MIPAS and co-located IMAA-CNR radiosonde and lidar data for 23 rd April H2 O (g/kg) E-3 1E Radiosonde H2 O (g/kg) Fig. 9: MIPAS versus IMAA-CNR radiosonde water vapor mixing ratio. Radiosonde data have been calculated as mean value in the altitude range corresponding the MIPAS altitude resolution. Each color corresponds to different investigate altitude range: in blue the 5-9 km range, in red the km and finally in green the altitudes higher than 13 km.

11 H2 O (g/kg) Lidar H2 O (g/kg) Fig. 10: MIPAS versus IMAA-CNR lidar water vapor mixing ratio. Lidar data have been calculated as mean value in the altitude range corresponding the MIPAS altitude resolution. Data related to an altitude range of 5-9 km are reported in blue, the ones relative to the km range are reported in red. For a more quantitative analysis, MIPAS data have been compared with mean values of radiosonde and lidar profiles calculated in the altitude window observed by MIPAS. In Fig. 9, MIPAS versus radiosonde water vapor mixing ratio data are reported. A total amount of 47 values are compared for the 14 days in which radiosonde and MIPAS version 4.61 data are available. In average a good agreement is observed for values higher than 0.01 g/kg, that corresponds in average to altitudes higher than 12 km. For lower water vapor content, MIPAS data seem to be poor sensitive to atmospheric variations. However, it is difficult to derive quantitative results, because of the poor reliability of the RS80-A Humicap sensor in the dry cold atmosphere. The same analysis has been carried out for comparisons with Raman lidar data. Among the 24 available cases reported in Tab. 6, the overlap between MIPAS and lidar profiles is found only for 16 measurements, for a total amount of 24 compared values. Fig. 10 reports MIPAS versus lidar water vapor mixing ratio for these data. Two areas can be distinguished in the scatter plot. The first is related to values, reported in blue, measured in the range of 4-9 km above sea level and is characterized by large differences between lidar and MIPAS data. Because of the large spatial variability of the water vapor at these altitudes, it is not possible to derive a more quantitative conclusion. The realization of a procedure to reduce MIPAS data at an altitude grid with a better vertical resolution also in this altitude range could be a significant improvement in the validation of these data. The second group of points collects values measured between 10 and 13 km above the sea level, reported in red. Also in this case, MIPAS seems to derive an almost constant value of water vapor content, on the contrary a natural variability in time and space of 0.02 g/kg has been observed in this altitude range by means of IMAA-CNR Raman lidar. In particular, MIPAS typically underestimates the km water vapor content with an underestimation ranging between g/kg in the km altitude range, with a mean value of g/kg. 4. CONCLUSION We have compared water vapor measurements performed by MIPAS with those of the MIAWARA microwave radiometer located in Bern, and with measurements performed by three lidar and radiosounding stations in Central-Southern Italy. MIPAS data have been compared to ground based measurements in the middle atmosphere (20-60 km) by means of the radiometer and in the UTLS with lidar and radiosonde profiles, covering the whole altitude range investigated by MIPAS. In the km altitude range, a mean overestimation ranging between 7-15% has been observed over 195 cases recorded by MIAWARA. Discrepancies up to 30-40%, observed in some of these cases, need further

12 investigations. Additional intercomparisons of MIPAS data with MIAWARA measurements together with aircraft and stratospheric balloon soundings could be performed using the dataset collected during the LAUTLOS campaign in early At lower altitude the intercomparison is complicated by the unavailability of the average kernel necessary for the reduction of MIPAS data to a closer altitude grid. In addition, the sharp gradient around the tropopause makes difficult and less accurate the MIPAS measurements at these altitudes. However, with the new software version, MIPAS profiles often reach altitude lower than 12 km: in the case of Potenza, for example, about 70% of MIPAS profiles available for the intercomparison, extend over the tropopause. Generally, there is a good agreement between radiosonde, lidar and MIPAS products, but, in the range of km, an underestimation of about g/kg has been observed in the MIPAS water vapor profiles respect to IMAA- CNR lidar measurements. This underestimation is confirmed by the mean difference of g/kg observed at the same altitudes between MIPAS and RS90, ISAC-CNR, radiosonde data. A lower MIPAS underestimation of g/kg has been found respect to RS80, IMAA-CNR, data. This is due to a residual underestimation in the RS80 data even after the performed correction for the dry bias in cold air. However, only 30% of MIPAS data in coincidence with University of L Aquila, ISAC-CNR and IMAA-CNR have been provided until the ACVE-2 meeting. More reprocessed data are needed to draw more quantitative conclusion for UTLS region. ACKNOWLEDGMENTS The University of L Aquila work have been partially funded by the Environment Program of the European Union, under contract EVR1-CT and by CETEMPS (Integration of remote sensing techniques and numerical modeling for the forecast of severe weather; The validation activity of the ISAC-CNR group within the ENVISAT Atmospheric Chemistry Validation Team, was partly supported by the Italian Space Agency. The IMAA-CNR activity for the validation of ENVISAT atmospheric products was partly funded by the Italian Space Agency and by PON , Misura II.1, MIUR. REFERENCES 1. Ceccherini S. and Ridolfi M., Averaging Kernels for MIPAS near real time level 2 retrievals, IFAC technical note, n TN-IFAC-OST0201, 2002 (available at 2. Ceccherini S., Averaging Kernels for MIPAS off line level 2 retrievals, IFAC technical note, n IFAC_GA_2004_01_SC, 2004 (available at 3. SPARC Assessment of Upper Tropospheric and Stratospheric Water Vapour, WCRP - 113, WMO/TD - N 1043, SPARC report N 2, December Deuber B. and Kämpfer N., Minimized standing waves in microwave radiometer balancing calibration, Radio Science, vol. 39, n. RS1009, doi: /2003RS002943, Deuber B., et al., A new 22-GHz Radiometer for Middle Atmospheric Water Vapour Profile Measurements, IEEE Transactions on Geoscience and Remote Sensing, vol. 42, n. 5, doi: /TGRS , Lindzen R. S., Some coolness concerning global warming, Bulletin American Meteorological Society, vol. 71, , Lindzen R. S., Response to Greenhouse warming and the tropical water budget, Bulletin American Meteorological Society, vol. 71, , Harries, J.E., Atmospheric radiation and atmospheric humidity; Q.J.Roy.Met.Soc.,vol. 123, , Leiterer U., et al., Method for Correction of RS80 A- Humicap Humidity Profiles, report German Weather Service, Meteorological Observatory Lindenberg, Am Observatorium 12, D Ansmann A., et al., Indipendent measurement of the extinction and backscatterprofiles in cirrus clouds, Applied Optics, vol. 31, 33, Goldsmith J.E.M., et al., Raman lidar profiling of atmospheric water vapour: simultaneous measurements with two collocated systems, Bull. Am. Meteorol. Soc. 75, , Rizi, V., et al., A combined Rayleigh-Raman lidar for measurements of tropospheric water vapour and aerosol profiles, Il Nuovo Cimento C, 21, 53-64, Rizi V., et al., Raman Lidar Observations Of Cloud Liquid Water, to appear in Applied Optics. 14. Congeduti F., et al., The multiple-mirror lidar 9- eyes, J. Opt. A: Pure Appl. Opt., vol. 1, pp , 1999.

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