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Maldives. The GPS antenna was installed at the site of the. GEOPHYSICAL RESEARCH LETTERS, VOL. 35, L13803, doi:10.1029/2008GL033764, 2008.
GEOPHYSICAL RESEARCH LETTERS, VOL. 35, L13803, doi:10.1029/2008GL033764, 2008

Verification of precipitable water vapor estimated from shipborne GPS measurements M. Fujita,1 F. Kimura,2 K. Yoneyama,1 and M. Yoshizaki1 Received 24 February 2008; revised 28 April 2008; accepted 12 May 2008; published 3 July 2008.

[1] Precipitable water vapor (PWV) was measured using a shipborne Global Positioning System (GPS) during a two month cruise in the equatorial Indian Ocean. More than 300 profiles were also observed by radiosondes released from the ship during the experiment. GPS atmospheric delay and PWV was estimated and compared to the radiosonde observations. The GPS-PWV is in good agreement with the radiosonde PWV (RS-PWV) with an rms error of 2.27 mm and a mean difference of less than 1 mm during the nighttime. In the daytime, the dry bias of RS-PWV becomes 3.63 mm. Thus GPS-PWV observed from a ship under way in the open ocean is sufficiently accurate. The ship based GPS-PWV data are accurate to be useful for numerical weather predictions as well as for the calibration of the satellite remote sensors. Citation: Fujita, M., F. Kimura, K. Yoneyama, and M. Yoshizaki (2008), Verification of precipitable water vapor estimated from shipborne GPS measurements, Geophys. Res. Lett., 35, L13803, doi:10.1029/2008GL033764.

1. Introduction [2] Atmospheric precipitable water vapor can be retrieved from the observations of a ground-based GPS with high accuracy and with high temporal resolution [e.g., Rocken et al., 1993]. Thousands of ground-based GPS sites have been set up all over the world. The accuracy of the GPS-PWV has been reported by many studies. Wang et al. [2007] investigated the accuracy of the GPS-PWV in comparison to RS-PWV and showed that the difference in bias between them strongly depends on the type of humidity sensor used in the radiosondes, which depend on the operational organization. For example, the standard deviation and bias (GPS - RS) were 0.47 mm and 0.33 mm, respectively, in Norway, and 2.60 mm and 2.42 mm, respectively, in Brazil. Although RS-PWV observed by radiosonde is often assumed to be a reference value for the validation of GPS-PWV, some humidity sensors have a systematic dry bias during the daytime, as documented well by previous studies [e.g., Vo¨mel et al., 2007]. [3] The estimation of PWV from a moving GPS platform faces the additional challenge that the coordinates of the receiving antenna have to be estimated simultaneously with the tropospheric delay. Position and PWV can be estimated in baseline mode relative to a fixed reference receiver. Over the open ocean, however, we have to use precise point positioning (PPP) [Zumberge et al., 1997] because of the 1 Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan. 2 Institute of Geosciences, University of Tsukuba, Tsukuba, Japan.

Copyright 2008 by the American Geophysical Union. 0094-8276/08/2008GL033764

great distance to any land-based reference point. PPP requires the availability of accurate GPS satellite position and clock information. In a previous experiment Rocken et al. [2005] determined PWV from a ship in the Caribbean sea for 2 weeks and found about 3 mm rms agreement with a ship-based water vapor radiometer and several radiosonde launches. The study presented in this paper is different from the previous one in several significant ways: (1) the cruise is much longer in time and reaching much more remote regions of the world’ s equatorial ocean – thus the results are representative of what can be achieved anywhere on Earth under varying atmospheric conditions; (2) the ship we used is much smaller than the cruise ship that hosted the Rocken et al. [2005] experiment – thus we had to estimate water vapor under conditions of more wave motion and our results should be representative of what can be achieved not only from ships but also from ocean buoys; (3) finally we launched many more radiosondes than the previous work – thus enabling us to establish solid statistics of RS-PWV comparisons for different parts of the diurnal cycle. [4] In the tropical oceans, strong tropical convection often leads to severe storms. In spite of the importance, some difficulty still remains in the precise observation of water vapor over the open ocean. The oceanic water vapor data obtained from the satellite-borne microwave radiometers (e.g., SSM/I, TMI) is very useful for the analysis of the spatial distribution of water vapor. However, the error in the estimation of the water vapor by the SSM/I was greater than 4 – 5 mm rms [Jackson and Stephens, 1995]. The basic observation of PWV over the ocean still strongly depends on radiosondes released from operational weather ships, but the spatial resolution is much lower than on land. We conducted an intensive shipborne experiment for two months which included GPS observation under various atmospheric conditions. Radiosondes were also launched during the experiment. This paper estimates the accuracy of the shipborne GPS-PWV and compares it to the RS-PWV.

2. Observation [5] An experimental cruise termed the ‘‘Mirai Indian ocean cruise for the Study of the MJO –convection Onset (MISMO)’’ was conducted around the Indian Ocean from October to December 2006 [Yoneyama et al., 2008]. The shipborne GPS observations were performed as part of the MISMO project. Figure 1 shows a navigation chart for the period when the radiosonde observation were carried out. The GPS antenna was installed facing the zenith on the deck in the stern of the 8,678-ton research vessel ‘‘Mirai.’’ During the MISMO, PWV was also observed by a GPS receiver at Gan island (GAN) in Addu Atoll, Republic of Maldives. The GPS antenna was installed at the site of the

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Figure 1. Navigation chart of MISMO cruise. The dots indicate the positions of the ship when radiosonde observations were performed. The ground observational site (GAN) is indicated by the star.

national meteorological office in Maldives. Both the installed receivers are Ashtech Z-Xtreme dual-frequency with Dorne Margolin choke-ring antennas. GPS data were recorded every five seconds. Radiosonde observation was performed three or six hourly on the Mirai and six or twelve hourly at the GAN station. The sensors used in all the soundings were the RS92 series manufactured by Vaisala. During the MISMO, we obtained 313 and 140 profiles from the Mirai and the GAN, respectively.

3. Data Analysis [6] GPS radio signals (L band at frequencies of 1.22760 and 1.57542 GHz) are delayed by components in the ionosphere and in the neutral atmosphere traveling from the GPS satellite to the GPS receiver. The delay due to the neutral atmosphere is usually scaled to zenith and called the zenith tropospheric delay (ZTD) [Bevis et al., 1992]. [7] A new commercial GPS analysis software, RTnet, was used for ZTD. RTnet is primarily designed for real-time applications, but it can also be used for post-processing [Rocken et al., 2006]. All GPS data were processed in PPP mode with the RTnet software. In PPP mode, RTnet requires accurate GPS satellite positions and clocks which we obtained from the Center for Orbit Determination Europe. We used 30-sec satellite clocks and interpolated them to the 5-sec GPS receiver sampling intervals. The availability of 30-sec or higher satellite clock corrections is important for the estimation of ship positions and ZTD. We estimated the ZTD every 5-sec together with ship positions, receiver clocks, and ambiguity parameters. The Saastamoinen [1972] model was used for estimating the a priori tropospheric delay. In order to separate vertical ship positions and the ZTD we used low elevation observations down to 3 degrees and the global mapping function (GMF) [Boehm et al., 2006]. The data are processed in forward filtering without backwards smoothing.

[8] The ZTD can be separated into two parts, i.e., the zenith hydrostatic delay (ZHD) and the zenith wet delay (ZWD). GPS-PWV is estimated from the ZWD and surface temperature at the GPS station [Bevis et al., 1992]. The ZWD is obtained by a simple difference between ZTD and ZHD. The ZHD is estimated from surface pressure and coordinate of the GPS station [Elgered et al., 1991]. RS-PWV is calculated by the integration of the specific humidity in each layer. Hourly averaged GPS-PWV is validated in order to adjust the timing of radiosonde observation.

4. Results [9] During the experiment, a drastic temporal change in the water vapor was observed over the Indian Ocean in the first ten days of November [Yoneyama et al., 2008]. The amount of water vapor first reduced due to a synoptic dry airflow. It was followed by an increase in the moisture, after which convection became active around the Indian Ocean, as shown in Figure 2a, which shows the Global-merged IR Brightness Temperature data provided by NASA. [10] In order to verify the accuracy of the RTnet software adopted in fixed stations, the ZTD was estimated at the GAN station in the same way as the ship estimation, allowing the coordinates of GAN to move freely. Also, the ZTD was estimated as a fixed station using the tightly constrained coordinates to validate the RTnet kinematic processing. The ZTD data were converted into GPS-PWV data using the surface temperature and pressure data at the GAN station. The PWV converted from ZTD estimated freely has insignificant bias and rms error comparing with the PWV estimated as a fixed station. [11] Figure 3 shows a scatter diagram of GPS-PWV and RS-PWV at GAN. During the nighttime, the GPS-PWV agrees well with the RS-PWV with an rms error of 1.49 mm, while mean difference between them is 0.20 mm. On the other hand, the Figure 3 shows a large discrepancy between

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Figure 2. (a) Time-longitude cross section of black body temperature in infrared range (TBB) along the equator, which represents the convective activity during the MISMO cruise. The black solid line indicates the position of the R/V Mirai. (b) The time series of the GPS-PWV (black dots) and the RS-PWV (gray crosses). The GPS-PWV was averaged over an hour. Both PWV data were not observed during the ship called at Male, Maldives. them during the daytime. As the results, rms error and mean difference of all data are 3.48 mm and 3.13 mm, respectively. The daytime dry bias of RS92 radiosonde is basically caused by solar radiation [e.g., Vo¨mel et al., 2007]. Considering poor agreement in the daytime, only the nighttime RS-PWV can be considered as a reference value. We can conclude that the ground-based GPS-PWV estimated by RTnet has a good accuracy which is comparable to those reported in previous studies [e.g., Wang et al., 2007]. [12] After the verification of the GPS-PWV on land, the PWV data obtained by the shipborne GPS were also verified. The ZTD was estimated using the kinematic PPP strategy and converted into GPS-PWV using the temperature and pressure observed on the ship. Figure 2b shows the time series of the PWV derived from the GPS and radiosonde on the Mirai. The GPS-PWV and RS-PWV showed similar changes during the cruise. The scatter diagram of the PWV detected by the GPS and radiosonde on the Mirai is illustrated in Figure 4. During the nighttime, GPS-PWV is in good agreement with the RS-PWV with an rms error of 2.27 mm and a mean difference of less than 1 mm. In the case of using all data, rms error and mean difference are 3.02 mm and 1.34 mm, respectively. The agreement

between the shipborne GPS-PWV and RS-PWV is slightly poorer than the ground-based one. During the MISMO, the maximum of the wave height was approximately 3 m. In relatively rough sea situation when wave height was more than 1.5 m, rms error between GPS-PWV and RS-PWV was 3.31 mm. The reason of poorer agreement of PWV obtained on Mirai might be large waves in rough sea situation.

5. Discussion [13] In this experiment, the significant daytime mean difference between GPS-PWV and RS-PWV was found in both the Mirai and GAN. Table 1 shows rms and mean difference for daytime (08:00, 11:00, 14:00, 17:00 Local Time: LT) and nighttime (20:00, 23:00, 02:00, 05:00 LT). During the daytime, they have a large mean difference of 2.45 mm and 3.13 mm at the Mirai and GAN, respectively. The maximum diurnal mean difference was 3.82 mm (14:00 LT) and 3.70 mm (11:00 LT) at the Mirai and at GAN, respectively. These differences seem to be a wellknown dry bias of the radiosonde humidity sensors. [14] Vo¨mel et al. [2007] mentioned that the relative difference between the relative humidity of RS92, which

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Table 1. Statistical Summary of the Difference Between the GPSPWV and RS-PWVa Site Mirai GAN

All

Daytime

Nighttime

rms

md

rms

md

rms

md

3.02 2.77

1.34 1.81

3.63 3.48

2.45 3.13

2.27 1.49

0.27 0.20

a The mean values of rms and mean difference (md) are indicated in all data, the daytime (08:00, 11:00, 14:00, 17:00 Local Time (LT)) and the nighttime (20:00, 23:00, 02:00, 05:00 LT). The unit of each value is mm.

Figure 3. Scatter diagram of the PWV for the GPS and radiosonde observed at GAN. The gray dots indicate the data in the daytime (08:00, 11:00, 14:00, 17:00 LT), while the black crosses indicate the data in the nighttime (20:00, 23:00, 02:00, 05:00 LT). The slope of the line is 1. is the same sensor used in our experiment, and that of Cryogenic Frostpoint Hygrometer is approximately 5 – 15% in the lower troposphere during the daytime. The difference in humidity is estimated to be approximately 1 – 5 mm in PWV, if the relative difference is assumed to be below 800 hPa in our sounding on the ship. This estimated difference in PWV (1 – 5 mm) is larger than the dry bias of radiosonde observed in this study. Vo¨mel’s dry bias of radiosonde might be intensified by the solar radiation reflected from the land. This can be observed from their radiosonde profile, which shows a dry bias even near lowest

layer (See their Figure 6). On the other hand, the comparison of relative humidity between RS92 and the Meteolabor Snow White chilled-mirror dew/frost-point hygrometers on the ship does not show a significant difference near the surface [Yoneyama et al., 2008, Figure 1]. Our hypothesis is that the effect of radiative reflection is smaller in the case of observations from a ship. In fact, the dry bias of radiosonde observed at the GAN was larger than that observed at Mirai. The daytime dry bias of the radiosonde data observed on ship and land does not contradict the values obtain in the previous studies. We can conclude that the GPS observation is not significantly biased. [15] Key advantages of GPS-PWV are higher accuracy and temporal resolution; however, until now these data have been obtained almost exclusively from fixed land-based sites. The present study shows that the accuracy of the shipborne GPS-PWV is almost the same as that of groundbased GPS-PWV even in fairly remote regions of the equatorial ocean. Accurate PWV data can be obtained anywhere over the ocean in the world by this method if GPS observing systems are installed in voluntary observing ships (VOS) or buoys in the future. No additional equipment, such as stabilized platforms for the antenna or inertial motion sensors, is required. High quality PWV data over the ocean would be useful for numerical weather predictions and for the calibration of remote sensors.

6. Conclusions [16] Precipitable water vapor was estimated using a shipborne GPS for two months, during which more than 300 radiosonde profiles were observed from the ship. The GPS atmospheric delay was estimated every five seconds by PPP analysis, which allows to obtain accurate coordinates instantaneously from the data observed by a single GPS receiver without reference stations. The estimated shipborne GPS-PWV data are of high quality. The GPS-PWV is in good agreement with RS-PWV with an rms error of 3.02 mm, while the RS-PWV shows a dry bias of 1.34 mm. The dry bias of RS-PWV becomes 3.63 mm during the daytime, which is in reasonable agreement with the dry bias of the radiosonde reported by previous studies. Nighttime observations of GPS-PWV are in good agreement with the RS-PWV with a bias of less than 1 mm. [17] It is difficult to observe PWV with high accuracy in the open ocean. The conventional PWV observations by satellite remote sensors have relatively lower accuracy and sampling frequency, but they can observe a wide area simultaneously. The present study validated that PWV estimated by the shipborne GPS has almost the similar accuracy as that estimated from ground-based GPS. Useful

Figure 4. Same as Figure 3 but for Mirai. 4 of 5

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information regarding PWV can be obtained by using the present method if GPS observational systems are installed on VOS or on buoys. Many regions of the Earth could benefit if accurate PWV data were available from upwind ocean regions. Japan, for example, could likely improve its precipitation forecast if high quality PWV data were available from the Sea of Japan to the west. Such oceanic PWV data could be utilized in numerical weather predictions as well as for the calibration of the remote sensors. [18] Acknowledgments. The authors would like to express their thanks to all members of the MISMO project. They are also grateful to Christian Rocken and Tetsuya Iwabuchi of GPS Solutions Inc. for their valuable suggestions and supports on this study.

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