Validation of near infrared satellite based algorithms to retrieve atmospheric water vapour content over land

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1 Rivista italiana di Telerilevamento , 41 (1): Validation of near infrared satellite based algorithms to retrieve atmospheric water vapour content over land Anna Serpolla 1, Stefania Bonafoni 1, Riccardo Biondi 2, Olivier Arinò 3 e Patrizia Basili 1 1 Dept. of Electronics and Information Engineering, Univ. of Perugia, via Duranti 93, Perugia. 2 SERCO c/o ESA/ESRIN via G. Galilei, Frascati, Italy 3 ESA ESRIN, Via Galileo Galiei, Frascati, Roma Abstract This paper presents the validation results of ENVISAT MERIS and TERRA MODIS retrieval algorithms for atmospheric Water Vapour Content (WVC) estimation in clear sky condition on land. The MERIS algorithm e ploits exploits the radiance ratio of the absorbing channel at 900 nm with the almost absorption-free reference at nm, while the MODIS one is based on the ratio of measurements centred at near 0.905, 0.936, and 0.94 µm with atmospheric window reflectance at and 1.24 µm. The e first r t test te t was a performed er rmed in n the t e Mediterranean ed terranean area usin n WVC provided from both ECMWF and AERONET. As a second step, the performances of the algorithms were tested exploiting WVC computed from radiosoundings (RAOBs) in the North East Australia. The different comparisons with respect to reference WVC values showed an overestimation of WVC by MODIS (root mean square error percentage greater than 20%) and an acceptable performance of MERIS algorithms (root mean square error percentage around 10%). Keywords: water vapour, near infrared, MERIS, MODIS, RAOB, ECMWF. Validazione di algoritmi di stima del vapor d acqua atmosferico su terra da sensori satellitari nel vicino infrarosso Riassunto In questo lavoro vengono presentati i risultati della validazione degli algoritmi implementati per i sensori MERIS a bordo di ENVISAT e MODIS sul satellite TERRA, per la stima di contenuto di vapore acqueo (WVC) atmosferico su terra in condizioni di cielo sereno. L algoritmo MERIS sfrutta il rapporto tra le radianze nel canale sensibile al vapore (900 nm) e quello trasparente (890 nm), rapporto utile per eliminare i contributi di riflettanza della superficie. L algoritmo MODIS, invece, si basa sul rapporto tra le misure nei canali intorno a 0.905, 0.936, 0.94 µm e quelli in finestra a e 1.24 µm. Inizialmente l analisi è stata svolta sull area del Mediterraneo utilizzando i dati ECMWF e AERONET. Successivamente un ulteriore valutazione delle prestazioni è stata ottenuta nell Australia Nord-Orientale confrontando i prodotti satellitari con il vapore ricavato da radiosondaggio (RAOB). Dallo studio emerge come il MERIS mostri buone prestazioni nella stima di WVC (errore percentuale intorno al 10%) mentre si evince la tendenza del MODIS a sovrastimare il vapore (errore 37

2 Serpolla et al. Validation results of MERIS algoritms for atmospheric WVC percentuale anche superiore al 20%). Parole chiave: vapore acqueo, vicino infrarosso, MERIS, MODIS, RAOB, ECMW. Introduction Water vapour is one of the most important atmospheric constituents which plays a crucial role in the Earth s natural greenhouse effect, water cycle and radiation budget. Determining its spatial and temporal distribution, essential for global climatic changes studies, is a difficult task because of its stron variability with time, location and altitude. In addition water vapour fluctuations are a major error source in the mismodelin of delay experienced by radio waves in propagating through the troposphere: this is the principal limiting factor in all space geodesy applications such as Global Positioning System (GPS) [Bevis et al., 1992, ], Synthetic Aperture Radar interferometry [Davis et al., Hanssen, anssen, anssen, anssen, anssen, 1999, 1999, 1999, 1999, 1999, ], satellite altimetry and so on. In fact these remote sensors receive electromagnetic signals slowed down by the presence of tropospheric humidity, resulting in a delay in the arrival time. As consequence, the electromagnetic excess path length due to the atmospheric water vapour has to be estimated with high accuracy and removed: for this aim usually microwave or optical passive sensors are employed to work together with radars to correct data [Elgered et al., 1991 Li et al., ]. Radiosoundings (RAOBs) enable to measure the atmospheric water vapour amount over land but they usually occur two or four times per day, hence these data offer a spare temporal and spatial sampling, inadequate to assess water vapour variability. On the other hand, groundbased water vapour radiometers (WVR) allow a high temporal resolution but the involved costs are prohibitive for a dense network of WVR, while by GPS ground receivers the WVC is estimated with a good degree of accuracy, using continuously operating GPS networks [Basili et al., 2001]. On the contrary satellite instruments enable global analysis of the Earth atmosphere by the use of different retrieval methods based on several spectral bands. This paper reports the validation results of two near-infrared algorithms to retrieve atmospheric Water Vapour Content (WVC) in clear sky conditions over land: the first al rithm has been designed for Medium Resolution Imaging Spectrometer (MERIS) on ENVISAT platform while the second one has been implemented for Moderate Resolution Imaging Spectroradiometer (MODIS) on TERRA satellite. The work purpose was to investigate their achievable retrieval accuracy. r t first te t test a was er rmed performed n in t e the ed terranean Mediterranean area, using as reference WVC values data provided by both the European Center for Medium range Weather Forecasting (ECMWF) and the AErosol Robotic NETwork (AERONET). A second test was carried out in the North East Australia exploiting WVC computed from radiosoundings (RAOBs). The different comparisons pointed out a systematic overestimation of WVC by MODIS and an acceptable accuracy of MERIS algorithm if a rigorous cloud screening is applied. MERIS instrument and algorithm MERIS (http://envisat.esa.int/handbooks/meris/) was launched from the Space Center in Kourou, French Guyana, in March 2002 on-board the polar orbiting Envisat satellite. It is a 68.5 field-of-view ima n passive spectrometer which measures the solar radiation backscattered by the Earth by lookin in a cross-track mode. MERIS operates in fifteen 38

3 Rivista italiana di Telerilevamento , 41 (1): spectral bands, located in the 390 nm nm part of the spectrum, all programmable in position and width: observations are nominally limited to the day side of the Earth. The instrument delivers two spatial resolutions data (300 m and 1.2 km), covering a swath of 1150 km at a nominal altitude of 800 km. The MERIS water vapour retrieval algorithm for both land and sea surface exploits the radiance ratio of MERIS channel at 900 nm, located within the water vapour absorption band, and the almost absorption-free reference at nm [Fischer et Bennart, Bennartz, ]. The radiance ratio of the absorption and the window channel is used to eliminate the surface reflectance and to obtain an estimation of atmospheric transmission with regard to water vapour. The aforementioned retrieval of WVC is more feasible on land surfaces, since above water surfaces as well as above clouds presents some limitations. Indeed, above water surfaces the water vapour determination is restricted by the low reflectance of the back round, while under cloudy conditions it is feasible but with a high degree of uncertainty, since the penetration depth of the incoming solar radiation is mainly governed by cloud optical depth and cloud geometrical thickness. For this reason, in this work the investigation was limited over land pixels in clear-sky conditions. Several studies have shown a good accuracy for this retrieval approach, with a typical root mean square (RMS) error around 10% over land [MERIS QWG, 2006]. The used MERIS WVC data, together with the associated cloud mask, are Level 2 data RR (Reduced Resolution), having a spatial resolution of 1.2 km 2 (http://envisat.esa.int/pub/ ESA_DOC/ENVISAT/MERIS/meris.ProductHandbook.2_1.pdf). MODIS instrument and algorithm MODIS (http://modis.gsfc.nasa.gov/index.php) is integrated on the Terra satellite (10:30 am UTC equator crossing time, descending node, sun synchronous near polar orbit) and Aqua satellite (1:30 pm UTC equator crossing time, ascending node, sun synchronous near polar orbit) as part of NASA s Earth Observing System (EOS) mission. It is a scanning radiometer which acquires measurements in 36 high spectral resolution channels between 0.4and 14.4 µm with spatial resolutions of 250 m (2 bands), 500 m (5 bands), and 1000 m (29 bands) at nadir. A ±55-degree scanning pattern at the TERRA orbit of 705 km achieves a km cross track swath and provides global coverage every one to two days. MODIS measurements are used in the retrieval of several land, ocean, atmospheric key parameters. The MODIS Near-Infrared WVC retrieval algorithm [Gao et Kaufman, ] exploits e ploits e ploits the observations of water vapour attenuation of near-infrared (NIR) solar radiation reflected by surfaces and clouds. Five MODIS channels are involved in this method, based on the ratio of measurements centered at near 0.905, 0.936, and 0.94 µm with atmospheric window reflectance at and 1.24 µm. the differential absorption technique shows [ r n Frouin et al., 1990, ], the t e ratio rat en a e en a es t e the rem val removal of t e the e ect effects of r ace surface reflectance var at n variation t with wavelengths. The strong absorption channel at µm is most useful for dry conditions, while the weak absorption channel at µm is most useful for very humid conditions, or low solar elevation. Again, the retrieval of WVC is more reliable over land surfaces, since above water surfaces and clouds presents some limitations. The overall atmospheric water vapour error over cloud-free land areas is expected to be around 10% (Gao and Kaufman, 2003). Again, such as for MERIS, our investigation was limited over clear sky land pixels. The used MODIS WVC data, together with the associated cloud mask, are Level 2 data (MOD05_L2), having a spatial resolution of 1 km 2 (http://modis-atmos.gsfc. 39

4 Serpolla et al. Validation results of MERIS algoritms for atmospheric WVC nasa.gov/mod05_l2/index.html). Validation methodology The validation of both MERIS and MODIS retrieval algorithms above land was performed using different available sources of WVC values. First, the Mediterranean area was chosen as test site, example of mid latitude zone, and 5 images of MERIS and 4 images of MODIS of July and August 2006 passing over Italy were employed. For the MODIS sensor, the Terra satellite was chosen, since its passage is closer to the ENVISAT one (within one hour). first source of reference data, the European Centre for Medium-Ran e Weather Forecasts (ECMWF, products were considered (forecast data), consisting of WVC values of July and August 2006 sampled on a regular grid with a spacing of 0.50 in latitude and longitude. For this test, the data set was composed of MERIS and MODIS products contemporary (within one hour) to ECMWF data, previously screened with the cloud masks to select only cloud-free pixels. To perform the comparison, each ECMWF WVC value was matched with the average of WVC values associated to the satellite pixels contained over a radius of 25 km around the ECMWF coordinates such a methodology allows to match the different spatial resolutions. A source of in-situ validation measurements available in this area was the sun photometer data collected by AERONET (http://aeronet.gsfc.nasa.gov/index.html) [ olben [Holben et al. 199 : 1998]: the values of WVC, provided each 15 minutes, were considered to be suitable to validate over a single pixel the water vapour content retrieved by satellite-based sensors. Finally, the North East Australia was chosen as second test site, showing tropical climate in the coasts but with deserts in the hinterland. RAOB observations were employed such as in-situ validation data for the WVC (Fig. 1), since launch time agrees with satellites overpass (within about 30 minutes). For MERIS algorithm validation, 64 cloud-free single pixel pi el comparisons were performed, coming from 30 images of January 2005, February 2005, March 2005, May 2005/2006 and August In the same way, MODIS algorithm validation was performed by 30 matches from 10 images of January 2005, February 2005 and August Figure 1 - Map of RAOB location in the North East Australia. The coastal launch stations are showed in black, in grey the hinterland ones. The acronyms indicates RAOB names. 40

5 Rivista italiana di Telerilevamento , 41 (1): Results It is worth mentioning that in some cases the comparison with ECMWF data points out an underestimation of MERIS algorithm. However this situation was found near cloudy areas and for this reason each image was studied in deep. This analysis suggested that MERIS cloud screening is not able to detect cloudy pixels as well as MODIS cloud mask: the limit of MERIS cloud mask was also verified in other cases [Vidot et al., 2008]. Far from clouds, MERIS algorithm shows a RMS error of cm (RMS error percentage of 11%, bias of cm) with respect to ECMWF WVC (Fig. 2, left panel). The comparison performed for MODIS algorithm (Fig. 2, right panel) produces a RMS error of cm (20%, bias of cm). Figure 2 - Comparison between WVC from satellite sensors (MERIS data on the left, MODIS data on the right) and WVC from ECMWF data in clear sky condition over land. Figure 3 - Comparison between WVC from satellite sensors (MERIS data on the left, MODIS data on the right) and WVC from AERONET sun photometer data in clear sky condition over land. The location of photometer stations is available via html. The WVC validation with AERONET sun photometer data is shown in Figure 3. The comparison remarks again how MODIS algorithm is less accurate than MERIS one, since MERIS RMS error was cm (7%, bias of cm) while MODIS RMS error was 0.61 cm (26.77 %, bias of cm), as expected [Albert et al., 2005 Mcatee e Maier, 2006]. 41

6 Serpolla et al. Validation results of MERIS algoritms for atmospheric WVC In the North East Australia (Fig. 1) the previous performances of the two NIR algorithms were confirmed. The MERIS al rithm produces an RMS error of 0.37 cm (26.2%, bias of cm), decreasing to (12%, bias of cm) when only hinterland RAOB were considered (Fig. 4). MODIS algorithm validation resulted in a RMS error of 0.80 cm (52%, bias of cm), as shown in Figure 5. Figure 4 - Comparison of WVC from RAOBs and from MERIS in the North East Australia (left panel). In the right panel only hinterland RAOBs are compared. Figure 5 - Comparison of WVC from hinterland RAOBs and from MODIS in the North East Australia (left panel). Right panel: inter-comparison among MERIS, MODIS, RAOB (x-axes: RAOBs data and name). Conclusion In this work the validation of MERIS and MODIS algorithms for the retrieval of WVC is presented. The agreement between MERIS and ECMWF is quite good far from clouds while MODIS shows a higher RMS error. The pixel validation performed by using AERONET data results in a better reliability of MERIS algorithm with respect to MODIS one, although the number of available observations for the analyzed period is low and additional data would be required. The comparison with RAOB WVC results in a systematic overestimation of MODIS al rithm and confirms acceptable performances for MERIS one, achievin d accuracy in hinterland areas with respect to coastal zones, where the contamination of sea 42

7 Rivista italiana di Telerilevamento , 41 (1): surface is present. The investigation indicates that the main error source between MERIS and reference data lies in MERIS cloud screening elaboration, whereas MODIS cloud mask seems to be more reliable in the cloudy pixel detection. Briefly this work yields d performances for MERIS WVC algorithm in clear sky conditions over land: these results suggest future applications for this product, also different from climate research. References Albert P., Bennartz R., Preusker R., Leinweber R., Fisher J. (2005) - Remote sensing of athmospheric water vapour using the Moderate Resolution imaging Spectroradiometer (MODIS). Journal of Atmospheric and Oceanic Technology, 22 (3): Basili P., Bonafoni S., Ferrara F., Ciotti P., Fionda E., Ambrosini R. (2001) - Atmospheric water vapour retrieval by means of both a GPS network and a microwave radiometer during an experimental campaign at Cagliari (Italy) in IEEE Trans. on Geosci. and Remote Sensing, 39 (11): Bevis M., Businger S., Herring T.A., Rocken C., Anthes R.A., Ware R.H. (1992) - GPS meteorology: remote sensing of atmospheric water vapour using the Global Positioning System. J. Geophys. Res., 97: Davis J.L., Herring T.A., Shapiro I.I., Rogers A. E., Elgered G. (1985) - Geodesy by radio interferometry: Effects of atmospheric modelling errors on estimates of baseline length. Radio Sci., 20: Elgered G., Davis J.L., Herring T.A., Shapiro I.I. (1991) - Geodesy by radio interferometry: Water vapor radiometry for estimation of the wet delay. J. Geophys. Res., 96: Fischer J., Bennartz R. (1997) - Retrieval of total water vapour content from MERIS measurements. Algorithm Theoretical Basis Document PO-TN-MEL-GS-0005, ESA- ESTEC. Frouin R., Deschamps P., Lecomte P. (1990) - Determination from Space of Atmospheric Total Water Vapour Amounts by Differential Absorption near 940 nm: Theory and Airborne Verification. Journal of applied meteorology, 29: Gao B.C., Kaufman Y.J. (1998) - The MODIS Near-IR Water Vapor Algorithm. Algorithm Theoretical Basis Document, ATBD-MOD-05, NASA. Gao B.C., Kaufman Y.J. (2003) - Water vapor retrievals using Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared channels. J. Geophys. Res, 108 (D13): Hanssen R.F. (1999) - High-resolution water vapor mapping from interferometric radar measurements. Science, 283: Holben B.N., Eck T.F., Slutsker I., Tanré D., Buis J.P., Setzer A., Vermote E., Reagan J.A., Kaufman Y.J., Nakajima T., Lavenu F., Jankowiak I., Smirnov. (1998) - AERONET A Federated Instrument Network and Data Archive for Aerosol Characterization. Remote Sensing Environ. 66:1-16. Li Z., Muller J.P., Cross P., Fielding E.J. (2005) - Interferometric suynthetic aperture radar (InSAR) atmospheric correction: GPS, moderate resolution imaging spectroradiometer (MODIS), and InSAR integration. Journal of Geophysical Research, 110, B03410, doi: /2004jb Mcatee B.K., Maier S.W. (2006) - A comparison of algorithms for Near-Real Time water 43

8 Serpolla et al. Validation results of MERIS algoritms for atmospheric WVC vapour retrieval from MODIS. International Journal of Remote Sensing, 27 (23): MERIS Quality Working Group (2006) - MERIS Products Quality Status Report MEGS7.4 and IPF 5. Version 1. Vidot J., Santer R., Aznay O. (2008) - Evaluation of the MERIS aerosol product over land with AERONET. Atmos. Chem. Phys. Discuss., 8: : Received 12/05/2008, accepted 23/01/

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