MERIS IPWV VALIDATION: A MULTISENSOR EXPERIMENTAL CAMPAIGN IN THE CENTRAL ITALY

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1 MERIS IPWV VALIDATION: A MULTISENSOR EXPERIMENTAL CAMPAIGN IN THE CENTRAL ITALY P. Ciotti,, E. Di Giampaolo, P. Basili, S. Bonafoni, V. Mattioli, R. Biondi, E. Fionda, F. Consalvi, A. Memmo, D. Cimini, R. Pacione 5, F. Vespe 6 Dept. of Electrical Engineering, Univ. of L'Aquila, 67 Poggio di Roio, L'Aquila, Italy, p.ciotti@ing.univaq.it, emidio@ing.univaq.it Dept. of Electronic and Information Engineering, Univ. of Perugia, via Duranti 9 65 Perugia, Italy, basili@diei.unipg.it, bonafoni@diei.unipg.it, mattioli@diei.unipg.it, biondi@diei.unipg.it Fondazione Ugo Bordoni (FUB), viale Europa 9, Roma, Italy, ermanno@fub.it, fernando@fub.it Centro di Eccellenza CETEMPS, Univ. of L'Aquila, L'Aquila, Italy, adelaide.memmo@pstabruzzo.it, nico.cimini@aquila.infn.it 5 Telespazio, Centro di Geodesia Spaziale "G.Colombo", 75, Matera, Italy, rosa.pacione@asi.it 6 Agenzia Spaziale Italiana (ASI), Centro di Geodesia Spaziale "G.Colombo", 75, Matera, Italy, francesco.vespe@asi.it ABSTRACT This paper reports the results of an experimental campaign carried out in the Central Italy, considering also part of the Tyrrhenian Sea. Integrated precipitable water vapour estimates obtained from measurements of multiple sensors were produced for a period of about one year, with the purpose of validating the corresponding MERIS estimates. The validation is performed both at specific locations and over an extended area, considering ground based instruments (microwave radiometers, GPS receivers, radiosoundings) and satellite borne radiomenters (Special Sensor Microwave Imager Radiometer, ENVISAT Microwave Radiometer). INTRODUCTION In the framework of the validation activity of ENVISAT instruments and, in particular, with reference to MERIS measurements of atmospheric water vapour, this paper reports the results of an experimental campaign carried out at four test sites in the Central Italy and considering also part of the Tyrrhenian Sea. Integrated precipitable water vapour (IPWV) estimates obtained from measurements of multiple sensors, namely multichannel water vapour microwave radiometers (WVR), GPS receivers, radiosondes (RAOB), and meteorological stations, were produced for a period of about one year, with the purpose of validating the corresponding MERIS estimates. The test sites in our geographical network of instruments comprise the Elba Island, Perugia, L'Aquila, and Pomezia. Table I reports information about the four test sites and the locally available instrumentation. TABLE I Geographic positions and instrumental facilities of the four Italian MERIS test sites Test sites Lat ( N) Lon ( E) Instruments Perugia..6 GPS, WVR(/ GHz), Elba Island.76. GPS, L Aquila.7.5 GPS, Pomezia.65. WVR (, / GHz), RAOB, In addition, the IPWV outputs of the PSU/NCAR mesoscale numerical prediction model MM5 V. were produced and collected for reference at each of the test sites []. To assess the MERIS performances over a land background, we present local comparisons of MERIS water vapour estimates performed at each test site considering the available ground-based instrumentation and the outputs of the MM5 model. Proc. MERIS User Workshop, Frascati, Italy, November (ESA SP-59, May )

2 In order to evaluate the performances also over a sea background, we make comparisons based on IPWV maps of extended areas produced, on the one side, by MERIS and, on the other side, by geostatistical interpolation of the measurements (performed over land) of the Italian network of GPS receivers and the measurements (performed over sea) of the satellite based Special Sensor Microwave Imager Radiometer (SSM/I). A further element of comparison comes from IPWV measurements performed by the ENVISAT Microwave Radiometer (MWR). COMPARISON OF MERIS IPWV TO MEASUREMENTS OF THE GROUND BASED INSTRUMENTATION Neglecting scattering and ice contributions and considering a dual-channel WVR, with one frequency mainly sensitive to water vapour (subscript ) and the other to the liquid (subscript ), IPWV is estimated as [], []: IPWV = a +a τ +a τ () where τ, are the atmospheric opacities at the two frequencies computed from the corresponding brightness temperatures and a i are statistical retrieval coefficients []. Besides to the radiometric estimation of IPWV, in this work we exploited also the GPS receivers belonging to the Italian network: Zenith Total Delay (ZTD) time series were produced by the GIPSY/OASIS II software run at the Centro di Geodesia Spaziale G.Colombo of Matera [5]. The ZTD is usually divided into two components, the Zenith Hydrostatic Delay and the Zenith Wet Delay [6]: ZTD = ZHD+ZWD () The hydrostatic component can be modelled [7] with high accuracy; this allow an accurate computation of the wet component ZWD by subtracting ZHD from ZTD. The IPWV is than computed using the relationship: IPWV = π ZWD () where the factor π is a function of various physical constants and of the mean temperature of the water vapour in the atmosphere and can be computed as in [6]. Alternatively monthly averaged values of π can be computed from historical data bases of radiosoundings available for the sites of interest []. As a first example of results, Fig. shows time series of the ground based estimates of IPWV obtained by means of the above mentioned techniques (WVR, GPS and MM5), at the Elba Island test site for a period starting with the first available MERIS IPWV products (October ) and lasting until January. In order to make a comparison, we averaged MERIS IPWV pixel values provided by the first standard ESA algorithm (that we will refer to as the old ESA algorithm) within a circle having a radius of.5 centred on the latitude and longitude of the ground based instrumentation. We considered both clear sky and cloudy overpasses and computed also IPWV standard deviations within the selected circle. The mentioned statistics for MERIS IPWV are shown in Fig. as red circles (mean values) with error bars (standard deviations) for the cloud free cases while the corresponding cyan symbols refer to cloudy conditions as identified by the MERIS cloud flag or by an estimated optical thickness grater than zero. Besides of the cloudy cases, when MERIS is supposed to measure integrated water vapour only above the cloud, also for clear sky conditions the old ESA algorithm appears to underestimate IPWV with respect to the ground based instrumentation. As an additional example, Fig. shows a similar comparison performed at the Pomezia test site. In this case RAOB measurements were available and they are represented by blue diamonds, while a GPS receiver was not present. The shown period starts on the 6 th of June,, when new look up tables were used for the MERIS IPWV algorithm (referred to as the new ESA algorithm), and lasts until the middle of September. Fig. summarizes the comparison performed at the four test sites, considering separately the old and new ESA algorithms. In the left panel MERIS IPWV mean values are plotted versus corresponding ground based estimates as stars with different colour for each site. The best fitting line is shown in red. An underestimation of the MERIS IPWV values computed by the old ESA algorithm is noticeable in this figure as well as in Fig.. This underestimation is corrected by the new ESA algorithm that produces higher values of MERIS estimates, shown as diamonds in the right panel of Fig.. A grater correlation with the ground based measurements is also appreciable from the scatterplot. The new linear best fitting is again represented by a red line.

3 .5.5 => October => November => December => January W VR (Elba Island) GPS_Gipsy MM5 MERIS stdev (cloudy) MERIS avg (cloudy) MERIS stdev (cloud free) MERIS avg (cloud free) HO_COLUMN [cm] Julian day (years /) Figure. Time series of IPWV from WVR (black line), GPS (blue line) and MM5 outputs (green line), measured at the Elba Island. MERIS estimates and their standard deviations are superimposed (red symbols: cloud free cases; cyan symbols: cloudy cases)..5 => July => August => September.5 IPWV [cm].5.5 WVR MM5 RAOB's MERIS std MERIS avg Julian day (year ) Figure. Time series of IPWV from WVR (black line), MM5 outputs (green line) and RAOB (blue diamonds) measured at Pomezia. MERIS estimates and their standard deviations are superimposed (red symbols).

4 IPWV [cm] from MERIS L'Aquila Perugia Elba Pomezia IPWV [cm] from WVR/GPS IPWV [cm] from MERIS L'Aquila Perugia Elba Pomezia IPWV [cm] from WVR/GPS Figure. Scatterplot of MERIS IPWV versus WVR or GPS ground based estimates. In the left panel stars correspond to the old ESA algorithm while in the right panel diamonds correspond to the new ESA algorithm for comparisons belonging to two different time periods. Black symbols refer to L Aquila, green ones to Perugia, blue ones to Elba and red ones to Pomezia sites. Finally, Table II reports some statistical details of the comparison for the old and the new ESA algorithms. TABLE II Statistics of the comparison of MERIS IPWV to WVR or GPS values measured at the four test sites IPWV MERIS - IPWV GBASED Linear Best Fitting Algorithm N samples Bias [cm] St. Dev [cm] Corr. Coeff. Slope Intercept Old_ESA New _ESA MERIS IPWV OVER SEA BACKGROUND: COMPARISON WITH SSM/I AND MWR MEASUREMENTS In order to assess the capability of MERIS in the estimation of IPWV over a sea background we considered comparisons to satellite microwave measurements of columnar water vapour obtained by both the SSM/I radiometer on board of DMSP satellites and the MWR on board of ENVISAT. The SSM/I is a conical scanning imaging radiometer operating in both polarizations at 9.5,.5 (only in vertical polarisation), 7, and 85.5 GHz, while the ENVISAT MWR is a nadir-viewing, two channel (.8 and 6.5 GHz) microwave radiometer providing an estimate of IPWV on a km diameter field of view. The SSM/I images used in this work were obtained from the NOAA SAA archive. The data were calibrated and geographically corrected, and a coastal mask was applied to avoid land background contamination in IPWV measurements. To infer IPWV over sea from the SSM/I brightness temperatures at different frequencies and polarisations, we have used the algorithm proposed by Gerard and Eymard [8]. Both SSM/I and MERIS IPWV maps have been produced with a spatial sampling of km in the North-South and in the East-West directions. We present results successive to the 6 th of June, obtained by the new ESA algorithm, limiting our analysis to clear sky conditions. Left panel of Fig. shows for comparison a scatterplot of IPWV retrievals from MERIS and from SSM/I data for ten passes (7 th June, 5 th July, th, th, th, th, rd and 7 th August, st and nd September ) over the Tyrrhenian Sea. Right panel shows for additional comparison a scatterplot of IPWV obtained from MERIS and from MWR for six passes (6 th and 7 th June, th, th, th and th August ) over the Tyrrhenian Sea. A low correlation and a MERIS IPWV underestimation with respect to the microwave sensors can be noticed in both panels. On the other hand, the comparison between the two microwave radiometer (SSM/I and MWR) retrievals, shown

5 in Fig. 5 relatively to data from eight passes (6 th and 7 th June, 5 th July, th, th and th August, st and nd September ) over the Tyrrhenian Sea, presents a fairly good agreement. IPWV from MERIS [cm] bias = [cm] std. dev. =.6758 [cm] corr. coef. =.888 n. samples = 75 IPWV from MERIS [cm] bias = -.89 [cm] std. dev. = 56 [cm] corr. coef. = 5 n. samples = 6 5 IPWV from SSMI [cm] 5 IPWV from MWR [cm] Fig.. Comparison of IPWV retrieved over the Tyrrhenian Sea. Left panel: from MERIS and from SSM/I data for ten passes. Right panel: from MERIS and from MWR data for six passes. IPWV from MWR [cm] bias = -.9 [cm] std. dev. =.67 [cm] corr. coef. =.95 n. samples = 7 5 IPWV from SSMI [cm] Fig. 5. Comparison of IPWV retrieved from MWR and from SSM/I data for eight passes over the Tyrrhenian Sea. Finally, we have performed an integration of IPWV estimates from SSM/I images (over sea) with IPWV retrievals obtained at the locations of the Italian network of GPS receivers (over land). The integration is based on the Kriging with trend interpolator, a geostatistical method that produces values on a regularly spaced grid from the irregularly spaced observations, taking also into account the IPWV dependence on the orography [9-].

6 As an example of qualitative comparison, Fig. 6 shows in the left panel the MERIS precipitable water vapour image of August rd at 9:5 GMT, while the right panel shows the map of IPWV values over land and sea obtained by Kriging interpolation of SSM/I and GPS estimates. Figure 6. Map of MERIS IPWV values over land and sea (left panel); comparison with a map of the Kriging interpolation of SSM/I and GPS IPWV values (right panel)). A similar IPWV distribution is appreciable by the common grey scale used in the two maps. Notice that the black areas in the left panel are due to missing data in the MERIS IPWV measurements. The preliminary results of our measurement campaign, performed within the ENVISAT validation activity, show that the MERIS water vapour product, generated by the standard ESA algorithm, underestimates IPWV values both over land and sea backgrounds. The new ESA algorithm produces estimates much closer to all the validation measurements performed over land, while the comparison performed over the Tyrrhenian Sea with respect to satellite based microwave radiometers is less satisfactory. REFERENCES G. A. Grell, J. Dudhia and D.R. Stauff, "A description of the fifth-generation Penn State/NCAR mesoscale model (MM5)", NCAR Technical Note, NCAR/TN-98+STR, 7, 99.. E. R. Westwater, F.O. Guiraud, Ground-based microwave radiometric retrieval of precipitable water vapor in the presence of clouds with high liquid content, Radio Science, vol 5, pp , 98.. P. Basili, P. Ciotti, and E. Fionda, Accuracy of Physical, Statistical and Neural Network Based Algorithms for the Retrieval of Atmospheric Water by Ground-Based Microwave Radiometry, Proc. of IGARSS 98, Seattle, U.S.A., pp. 8-, July P.Basili, S. Bonafoni, R. Ferrara, P. Ciotti, E. Fionda, R. Ambrosini, Atmospheric Water Vapour Retrieval by Means of both a GPS Network and a Microwave Radiometer During an Experimental Campaign at Cagliari (Italy) in 999, IEEE Trans. on Geosci. and Remote Sensing, vol. GE-9, pp 6-,. 5. F. H. Webb and J. F. Zumberge, "An introduction to GIPSY/OASIS II, JPL D-88, M. Bevis, S. Businger, S. Chiswell, T.A. Herring, R.A. Anthes, C. Rocken and R.H. Ware, GPS meteorology: mapping zenith wet delays onto precipitable water, Journal of Applied Meteorology, vol., pp , March J. Saastamoinen, Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites, in the Use of Artificial Satellites for Geodesy. Geophys. Monogr. Ser., vol. 5, pp. 7-5, E. Gerard, L. Eymard, Remote Sensing of integrated cloud liquid water: Development of algorithms and quality control, Radio Science, vol., pp. -7, March-April N. A. C. Cressie, Statistics for spatial data. New York: John Wiley & Sons, 99.. P. Basili, S. Bonafoni, V. Mattioli, P. Ciotti, F.S. Marzano, G. d Auria, N. Pierdicca and L. Pulvirenti, Mapping of precipitable water vapour by integrating measurements of ground-based GPS receivers and satellite-based microwave radiometers, Proc. of IEEE/IGARSS, Toronto, Canada, -8 June,.. P. Basili, S. Bonafoni, V. Mattioli, P. Ciotti, N. Pierdicca and L. Pulvirenti, Comparing model analysis and remote sensing estimation of water vapour field over the Tyrrhenian area, Proc. of Tyrrhenian International Workshop on Remote Sensing, Elba Island, Italy, pp , September.