GPS Meteorology Activities in the Malaysian Peninsula

Transcription

1 1 GPS Meteorology Activities in the Malaysian Peninsula Amir S. 1 and Musa T.A. 1 1 UTM-GNSS & Geodynamics Research Group, Infocomm Research Alliance, Faculty of Geoinformation & Real Estate, Universiti Teknologi Malaysia (UTM), Skudai, Johor MALAYSIA Tel: Fax: asharifuddin2@gmail.com, tajulariffin@utm.my Abstract The low latitude region experiences large amounts and inhomogeneous of atmospheric water vapour. In this region, the amount of water vapour distribution is difficult to determine due to the lacking of accurate, dense and continuous observation of water vapour data. The Global Positioning System (GPS) has the ability to provide continuous observations of water vapour, better spatial distribution, accurate and work under all weather condition. This paper presents some activities that have been conducted for GPS water vapour estimation in the Peninsular Malaysia, which is located in the low latitude region. Results from these activities have shown a potential capability to develop a (near) real-time GPS water vapour system in Peninsular Malaysia. Keywords: GPS; Integrated Water Vapor; Low-Latitude Region; Continuously Operating Reference Station 1. Introduction Water vapor plays a fundamental role in meteorological processes that act over a wide range of spatial and temporal scales. First it plays a fundamental role in the hydrological cycle. In brief, water vapour from the sea and land to the atmosphere where cloud form. From cloud, rain and snow fall back to the Earth s surface, thus supplying rivers, which flow back to the sea (Moran et al., 1997). Second it is the dominant greenhouse gas in the atmosphere. The greenhouse gas can lead to global warming. Then, it is both a symptom lead to a cause of the atmospheric greenhouse effect. Generally, the amount of water vapour of the atmosphere increases with temperature. The additional water vapour traps more of the heat energy from sunlight that escapes from the Earth. This trapped of the heat energy making a warming to the Earth s surface. A number of studies have shown that GPS meteorology offers detailed coverage and continuous observations regardless of weather conditions (e.g., heavy rainfall and clouds) and is an economical tool to complement other remote-sensing techniques to measure water-vapor content (Geurova, 2003; Bai, 2004; Tao, 2008). In fact, these studies have focused on midlatitude and near-tropical areas where CORS are well-established (e.g., the USA, Japan and

2 2 Europe; Haan, 2006). However, only a few studies have been conducted in the tropics. This situation is rather unfortunate because much of the wide range of spatial and temporal activities of the Earth s atmospheric water vapor occurs in the tropics (see Figure 1). This fact validates the notion that research need to be focused in the low latitude regions. This phenomenon is in many ways unique for researchers interested in the Earth s climate and operational meteorology, and challenging area for meteorological activities. Figure 1: Global IWV as derived from the NASA Water Vapour Project (NWAP). (Source: This paper will review the activities of GPS meteorology in the tropics with a focus on Peninsular Malaysia. Since 2008 at the UTM-GNSS & Geodynamics (G&G) Research Group, activities related to the GPS meteorology have grown up. In particular, studies on the GPS IWV estimation, comparison of GPS- and radiosonde-derived IWV and derivation of mean temperature (T m ) for Peninsular Malaysia. Currently, the activities of the G&G group have been extended on the development of (near) real-time IWV system in Peninsular Malaysia for operational weather forecasting which the design of the real-time system is reported. 2. GPS-Signal Propagation Delays and IWV Reduction Atmospheric refraction (or atmospheric delay) of GPS signals travelling from a satellite to the receiver on the earth s surface is mostly due to the earth s ionosphere and troposphere (Hofmann-Wellenhof et al., 2001). Because of the dispersive nature of the ionosphere, ionospheric delay can be directly measured using dual-frequency GPS receivers. Therefore, this paper deals with tropospheric delay only. 2.1 Calculation of GPS-derived IWV According to Bevis et al. (1992), the total ZPD can be obtained by 0 h 0 w ZPD ΔL M θ ΔL M θ (1) where h w 0 ΔL h is the Zenith Hydrostatic Delay (ZHD), 0 ΔLw is the Zenith Wet Delay (ZWD), θ is the satellite elevation angle, M h is the hydrostatic mapping function and M w is the wet mapping function. Elgered et al. (1991) created a model for ZHD estimation that is based on the

3 Saastamoinen model with the additional surface pressure ρ s divided by a factor f (θ, h), where h and θ are the heights above the ellipsoid and the latitudinal variation of the gravitational acceleration, respectively: ρ ZHD ( ) s (2) f θ, h where 2 0. h f (, h) cos (3) The GPS-derived IWV can be computed by subtracting ZHD in Eq. (2) from the total ZPD in Eq. (1) to produce ZWD value, which is subsequently multiplied by a conversion constant K : IWV K ZWD (4) where 3 K Here, k T 3 m 10 6 ' k 2 R v. (5) T (6) m T s and k 3 = (3.776 ± 0.004)e 5 (K 2 /mbar), k 2 = (17 ± 10) (K/mbar) and R v is a gas constant for the water vapor. T m is the weighted mean temperature of the atmosphere (Davis, 1985). The linear regression in Eq. (6) was derived from the radiosonde data and the surface temperature data T s (in Kelvin, K) (Bevis, 1992) and is commonly used in GPS-derived IWV calculations. It should also be noted that if the conversion constant K in Eq. (5) is divided by the density ( w =1000 kg/m 3 ) of liquid water, the result will be decreased by about 1/6. This is the typical ratio of the water-vapor path divided by the wet delay. 3. Activity 1: GPS IWV Estimation for Peninsular Malaysia Four GPS CORS network (known as MyRTKnet) operated by the Department of Survey and Mapping Malaysia (DSMM) were chosen for this study (e.g., PEKN, GETI, BANT and USMP; see Figure 2) because of the availability of nearby meteorological stations (e.g., KUAN, KTBR, KLIA and BYLP) that are operated by the Malaysia Meteorological Department (MMD). These meteorological stations are equipped with surface meteorological sensors and radiosonde balloons are launched twice daily (at 08:00 and 20:00 local time). Table 1 shows the distance between the MyRTKnet stations and the nearby radiosonde stations.

4 4 Figure 2: The locations of the MyRTKnet, meteorological and IGS stations utilized in this study. Table 1: Distance and height differences between the MyRTKnet and the nearby radiosonde stations. GPS station Radiosonde stations Distance Height Diff. (m) (km) (GPS - radiosonde) PEKN KUAN GETI KTBR BANT KLIA USMP BYLP Data Acquisition and Processing Strategies GPS observation data for the PEKN, GETI, BANT and USMP stations were obtained at 30-second intervals for 24 hours for the entire year Meanwhile, the surface temperature and pressure data, together with radiosonde data for the KTBR, KUAN, KLIA and BYLP stations, were provided by the MMD. In addition, GPS data from the International GNNS Service (IGS) stations in the tropics (see Figure 2; the stations are BAKO in Indonesia, NTUS in Singapore, IISC in India, PIMO in the Philippines, KARR in Australia, and COCO in Coco Island) were added during the GPS data processing. This is because precise ZPD can only be estimated when the GPS network covers a reasonably large area and the same satellites are therefore observed from different elevation angles at each GPS station (Duan et al., 1996; Zhang and Lachapelle, 2001). All GPS data from the IGS stations used in this study were downloaded from ftp://garner.ucsd.edu. The GPS data were post-processed using Bernese 5.0 software. In order to obtain highquality ZPD estimates, the GPS-data processing parameters and models were carefully configured as listed in Table 2. The ZPD of the GPS stations were estimated every hour within a 24-hour session. These estimations may be sufficient for climate study of monsoon season in Peninsular Malaysia and also to reduce the computation load from a long observation period.

5 5 Table 2: Parameter-setting and models for data processing. Processing parameters Processing strategy Input data Daily Network design OBS-MAX Elevation cut-off angle 3 Weighting of the GPS observables cos 2 (z), z = zenith angle Sampling rate seconds Orbits / EOP IGS final orbits (SP3) and EOP (Earth Orientation Parameters). Station coordinates Tightly constrained to the ITRF2005 reference frame. Absolute antenna phase center corrections PHAS COD.I05, SATELLIT.I05 Ocean-loading model FES2004 Ionosphere Double-difference Ionospheric-Free (IF) linear combination. Ambiguities solution Fixed, resolved using QIF strategy Ionosphere model for ambiguity fixing Global ionosphere model from CODE. Gradient Estimation Horizontal gradient parameters: tilting (24 hours interval). A-priori model A-priori Saastamoinen model (hydrostatic part) with the dry Niell mapping function. Mapping Function Wet-Niell mapping function (1-hour interval). Relative Tropospheric Constraints Loose ZPD Estimates 1 hour 3.2 GPS-derived IWV at the MyRTKnet Stations The GPS-derived IWV for the four MyRTKnet stations were calculated from the estimates ZPD using Eq. (1-6) and surface pressure and temperature data were interpolated using meteorological data from nearby weather stations.

6 6 Figure 3: GPS-derived IWV for the PEKN, GETI, BANT and USMP station. Figure 3 shows the daily GPS-derived IWV at from the PEKN, GETI, BANT and USMP stations, respectively, for the 1-year study period. It is notable that all MyRTKnet stations produced high and short term variability of the IWV values; this is common in lowlatitude regions due to high amounts and variability of water vapor.

7 7 4. Activity 2: Comparison of GPS- and radiosonde-derived IWV In this section, the GPS-derived IWV values from each MyRTKnet station are compared with data retrieved from water-vapor radiosondes. In the statistics shown in Table 3, the differences between the GPS-derived IWV and the radiosonde-derived IWV vary from to kg/m 2 depending on the location of GPS stations. Their linear correlation coefficients also vary from to Such results are comparable with the results obtained by Ohtani and Naito (2000) and Liou et al. (2001); however, they are slightly difference than the reported value (1-2 kg/m 2 ) for dry regions (Rocken et al., 1995; Emardson et al., 1998; Tregoning et al., 1998). This signifies the importance of studies focused on tropical regions. Table 3: Statistical properties of IWV differences (GPS - radiosonde). Station Min Max Mean RMS Corr PEKN GETI BANT USMP Activity 3: Derivation of Mean Temperature for Malaysian Peninsula T m is a key parameter to estimate IWV from ground-based GPS signals of ZPD. The T m (as shown in Eq. 6), was determined by Bevis et al. (1992) and is used globally by many researchers. However, this T m might not be a proper fit for Peninsular Malaysia because of the tropical climates around-years. Suresh et al. (2007) suggested that better results would be obtained by generating the T m model on a regional basis. This study aims to derive best estimate of T m value for Peninsular Malaysia. The T m was derived by using two years radiosonde data (2008 to 2009) from 4 meteorological stations located in the west and east coast of Peninsular Malaysia. Through the specific level data of the radiosonde observation using temperature, pressure, the dew-point temperature, height above MSL to calculate the T m. A commonly used method for estimating T m is to apply the relationship between T m and T s, since T s is obtained from surface temperature at meteorological surface measurement. The relationship between them are found as T m = 0.35 (T s ) Figure 4 is its statistics diagram. It was found that the estimation of T m for Peninsular Malaysia is 285K with small variations of 1-2K.

8 8 Figure 4: Regression diagram of the T m with the T s for Peninsular Malaysia 6. Activity 4: Looking Ahead- Real Time Water Vapour Estimation One of the main goals of this study is to establish the real-time IWV system for research, education, and operational weather forecasting. Several issues had to be addressed in order to meet this goal: i) Design of GPS Network, ii) GPS Data Handling, iii) Choice of Orbits, iv) Acquisition of Surface Meteorological Data, v) Type of Software, vi) IWV Data Delivery, vii) IWV Data Visualization and viii) GPS ZPD and IWV Data Validation. These will be discussed below: i. Design of GPS Network A GPS network called ISKANDARnet consist of three GPS stations distributed over the metro-area of Iskandar Malaysia, Johor is being established mainly for real time surveying applications. The ISKANDARnet1 (ISK1) GPS station is located in Universiti Teknologi Malaysia (UTM) while ISKANDARnet2 (ISK2) in Port of Tanjung Pelepas (PTP) and ISKANDARnet3 (ISK3) in Kolej Komuniti Pasir Gudang (KKPG). This study extends the applications of the GPS stations to be used for meteorology applications. Furthermore, the ISK1 station also equipped with a surface meteorological sensor which collects and records the meteorological data (see Figure 5). Figure 5: ISK1 GPS station located adjacent to the surface meteorological sensor.

9 Moreover, the DSMM has set up a network of approximately 50 MyRTKnet GPS stations in Peninsular Malaysia. Perhaps, with a resource sharing agreement between UTM and DSMM, all the GPS stations will be included in the real-time data processing in order to increase number of available observations, which will allow for an increased temporal and spatial resolution of IWV estimations. However, without such agreement both spatial and temporal resolution of the IWV estimations would be limited to the ISKANDARnet network only and not be dense enough for meteorological applications. Additionally, six existing stations from IGS in low latitude region (BAKO, NTUS, IISC, PIMO, COCO and KARR) will be included in order to extend the size of the network for absolute troposphere estimation. 9 ii. GPS Data Handling One hour batches GPS Receiver Independent Exchange (RINEX) files belonging to IGS, MyRTKnet and ISKANDARnet stations are retrieved via FTP from IGS, DSMM and UTM data centres (or servers), respectively. There is currently a limitation in the data retrieval due to the delay in the availability of the hourly GPS RINEX files. The start time of the data retrieved need to be chosen in order to process as many GPS stations as possible but without degrading too much time delay of delivering the real-time IWV results. Therefore, the GPS RINEX files retrieved begins at 20 minutes after the full hour of the data recording period. Once the hourly GPS RINEX files are received, they are put directly into the specific directory. iii. Choice of real-time orbits To fulfil the requirement of delivering the IWV estimates in real-time, the satellite orbit and clock information is acquired from the analysis centres of the IGS called the IGS ultra rapid orbit (IGU). This orbit is delivered 4 times per day or updated every 6 hours. The ultra rapid orbit file will be downloaded automatically, whenever new updates became available from the IGS data centres (ftp://cddis.gsfc.nasa.gov/gps/products/). iv. Acquisition of Surface Meteorological Data As mention above, the ISK1 GPS station equipped with surface meteorological sensor. The surface meteorological sensor observes of pressure, temperature, humidity, wind and rain data. All the surface meteorological observations at the ISK1 GPS station are automatically uploaded every 15 minutes to the specific directory. Then, the meteorological data will be downloaded to determine the IWV from the estimated ZPD using Matlab programming software. Besides, the surface meteorological sensor is not available for most of the GPS stations. Alternatively, the surface meteorological observations from the nearby weather station of the meteorological agency will be used. All surface meteorological observations from each weather station are automatically uploaded every 15 minutes period to the MMD agency. The meteorological observations such as pressure and temperature will be acquired from the MMD agency, and they have to be interpolated to the GPS stations for the ZPD to IWV transformation. v. Software The GPS observations data will be processed with Bernese GPS software under a network least squares estimation approach. The software is a highly accuracy, highly flexible suite of programs designed for post processing GPS data. Although the Bernese GPS software was initially designed for post processing applications, the software is controlled with the source code which gives the chance to modify the software for specific purpose. Thus, the

10 10 modifications will be implemented into the software which is the ability to utilize IGS ultra rapid orbit and produce ZPD parameters in real-time mode. vi. IWV Data Delivery 5 ZPD values will be estimated for each hour, retrieving IWV is carried out in MATLAB using the algorithms developed by Saastamoinen and Bevis (see Eq 1 to 5). Once the 5 IWV results data have been calculated, they will be stored into a file of specific directory and then will be sent to the meteorological agency within a target of timeliness 1 2 hours for operational weather forecasting. This file will be continually updated for each hour of IWV results. vii. IWV Data Visualization Additionally, a series of programs will be developed using MATLAB to visualize realtime GPS IWV onto 2D water vapour maps. The development of the 2D water vapour maps is essential for operational weather forecasting since they are desirable tool to give a better understanding of the moving water vapour for forecasting community. The 2D water vapour maps will be available in the dynamical web site. Also, this web site will be updated automatically for each 1 batch hour of latest IWV results. viii. GPS ZPD and IWV Data Validation As soon as the IGS final orbits are available, the quality of real-time ZPD estimation are evaluate with those obtained from post-processing ZPD estimation using daily data batches with the highest accuracy. Besides, in order to prove further the quality of real-time IWV estimate, its validity is determined by comparisons with radiosonde IWV results calculated at 4 stations were available nearby GPS stations. If the estimated IWV value exceeds to 2kg/m 2, the corresponding IWV is identified as questionable and need to be investigated. 4. Conclusions This paper presents the activities of continuous GPS IWV estimates for Peninsular Malaysia. This area experiences large amounts and inhomogeneous of atmospheric water vapour. The results show that the differences between the GPS-derived IWV and the radiosonde-derived IWV vary from to kg/m 2. Moreover, the newly derived T m should satisfy for GPS Meteorology application and reflects local weather condition in Peninsular Malaysia. Furthermore the designed of the real-time IWV system will allow for an increased temporal and spatial resolution of the IWV products. This designed also close to realtime availability of IWV estimates which is an urgent need for GPS contributions to operational weather forecasting. Acknowledgments This research was supported by Fundamental Research Grant Scheme (FRGS-78548) from the Ministry of Higher Education (MOHE) Malaysia. The authors wish to thank the Department of Survey and Mapping Malaysia (DSMM) and the Malaysia Meteorological Department (MMD) for providing the GPS and meteorological data, respectively. Thanks are extended to the International GNSS Service (IGS) and the Korea Astronomy and Space Science Institute processing center for GPS data sources and ZPD comparisons.

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