Metocean Forecast Verification for Erb West Platform over South China Sea

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2 Metocean Forecast Verification for Erb West Platform over South China Sea Ambun Dindang, Salleha Seth and Wan Azlina bt. Wan Abd Aziz The Malaysian Meteorological Department, Jalan Sultan, 46667, Petaling Jaya, Selangor, Malaysia, ABSTRACT This verification study is done for the Erb West platform, an oil and gas exploration site, located at latitude 6.3 North and longitude East, approximately 83 km westnorthwest of Kota Kinabalu, Sabah. The forecast data used in this study are surface wind speeds (WSPD) taken from the Global Forecast System (GFS), while the significant wave heights (SWH) and wave periods (WPRD) are from the Malaysian Meteorological Department Wave prediction Model (MMD WAM). These modeled data are then compared against the observed from the instruments at the platform for the period from 1 st January 2010 until 31 st December The bias and root-mean-square errors (rmse) for the 24-hr, 48-hr, 72-hr and 96-hr forecasts are then analyzed and scatter diagrams are plotted. The temporal error variability and temporal evolution of rsme are plotted. The model error for SWH between and 0.27 meters, are comparable to the T/P altimeter accuracy (smaller than 0.5 m), which indicates the the capability of MMD WAM model in predicting the SWH at Erb West Platform. The GFS model is not perform well in predicting the WSPD at Erb West platform. Keywords: Wave prediction Model (WAM), root mean square error (rsme), Erb West Platform

1. INTRODUCTION The South China Sea (SCS) is a semi-enclosed tropical sea located between the Asian land mass to the north, Peninsular Malaysia to the west, the Philippines Islands to the east,

3 1. INTRODUCTION The South China Sea (SCS) is a semi-enclosed tropical sea located between the Asian land mass to the north, Peninsular Malaysia to the west, the Philippines Islands to the east, Borneo to the southeast, and Indonesia to the south, with a total area of 3.5 x 106 km 2. The SCS is under the influence of monsoon winds and synoptic systems such as tropical cyclones that form over tropical Pacific Ocean and move across the Philippines and majority of it reaches SCS. From November to March, the northeasterly winter monsoon winds blow mainly from the northeast direction with speeds of near 10m/s over the whole SCS. From May to August, the southwesterly summer monsoon winds result in mainly southwesterly winds of approximately 8 m/s in the southern SCS and 4 m/s in the northern SCS (Peter C. Chu et.). Highly variable winds and surface currents are observed over SCS during the transitional periods (April and September). The oil and gas exploration platforms are located over the waters of Malaysian Exclusive Economic Zone (EEZ), an area beyond and adjacent to the territorial sea of Malaysia, extends to a distance of two hundred nautical miles (370 kilometers) from the baselines from which the breadth of the territorial sea is measured, Three regions namely Peninsula Malaysia Operation (PMO) - the waters off coast east of Peninsular Malaysia, Sabah Operation (SBO) waters off coast of west Sabah and Sarawak Operation (SKO)- covering the waters off coast of Miri and Bintulu, Sarawak (Figure 1), are the areas where the platforms are located. Figure 1. Location of Erb West platform marked by red circle. 1

4 In this study, we carried out the forecast verification for the Erb West platform located in the Sabah Operation (SBO) area, at latitude 6.3 o North and longitude o East, approximately 83 Km West of Kota Kinabalu, Sabah, marked by red circle in Figure 1. The site specific forecasts for Erb West platform are issued twice daily at about 0600hrs and 1800hrs local time. The Erb West platform is an oil and gas drilling platform belonging to the Petronas Carigali Sdn. Bhd. (PDSB), a company based in Kuala Lumpur, Malaysia. 2. LITERATURE REVIEW At present, the WAM (WAve prediction Model) model is widely used as a research tool and it is used operationally in global and regional implementations to make forecast of sea state useful for many applications such as offshore activities and ship routing. The capabilities of WAM have been assessed in detail (WAMDI Group 1988; Komen et al. 1994), giving confidence in its performance. A systematic verification study by Zambresky (1989), using conventional buoy data, and Romeiser (1993), using Geosat altimeter data, both concluded that, in general, the modeled wave heights [obtained by forcing WAM with European Centre for Medium-Range Weather Forecasts (ECMWF)] showed good agreement with the data. Both authors found that, during the Southern Hemisphere Winter, WAM may underestimate wave height by about 20% in large parts of the Southern Hemisphere and the tropical regions, while for the rest of the time agreement with data is fairly good. The validation of WAM Wavewatch-III Using the TOPEX/POSEIDON (T/P) over the South China Sea (SCS) for the whole year 2000 by Peter C.Chu et al. (2003) had found five conclusions. In their study, they concluded that (1) WAM Wavewatch-III simulate the seasonal variability of significant wave height reasonably well comparing to the T/P SWH, (2) the model errors for significant wave height hindcast have Gaussian-type distribution with mean values of 0.02 m, (3) the model errors of WWATCH-SCS have spatial variability with over prediction of the significant wave height except on the shallow continental shelf, (4)over the whole SCS, WWATCH has very low bias (-0.01 to 0.04 m) in predicting significant wave height and (5) the model errors are comparable to the T/P altimeter accuracy (0.5 m) in the central SCS and smaller than the T/P altimeter accuracy in the northern and southern SCS. 2

5 3. DATA The modeled data for WSPD are taken from the Global Forecast System (GFS), a global numerical weather prediction system containing a global computer model and variational analysis. It run four times a day and produces forecasts up to few days in advance. Meanwhile, the SWH and WPRD data are from the MMD WAM model. The onsite WSPD, SWH and WPRD are from the instruments reading located at platform. Chapters below described in detail about the data source. a. Model Data Grid Analysis and Display System (GrADS) are being used to download the WSPD from GFS, SWH and WPRD from the MMD WAM model four times daily. This modeled data are downloaded approximately at about 0200hrs, 0800hrs, 1400hrs and 2000hrs local time and run operationally at the Central Forecast Office of the Malaysian Meteorological Department. The Visual Basic for Editor (VBA) is used to generate the site specific forecast for the Erb West platform and issued via at about 0600 hrs and 1800 hrs daily. b. Observations The onsite observation data for the whole year 2010 were from the instruments reading attached to the Erb West platform and ed to our department daily for compilation and data checking. These instruments are installed and maintained by the officers at the platform itself. The RM Young wind monitor is used to record the surface wind direction and speed; and Enraf waveguide sensor for the significant wave height and wave period. These data are being collected every 10 minutes. 3

6 4. METHODOLOGY OF VERIFICATION The 24-hr, 48-hr, 72-hr and 96-hr forecasts of WSPD, SWH and WPRD were generated at the location of the Erb West platform at every 12-hr by downloading the modeled data from GFS and MMD WAM models. These forecasts data are then compared against the observations provided by the Erb West platform. It should be noted that observations of wind speeds, significant wave height and wave periods are averages in time at the location of platform while the model forecasts are expected values of wind speed (WSPD), significant wave period (SWH) and wave period (WPRD) over an area (the model grid box) and a time period (the model time step). In this study, the continuous verification method is used to verify the forecast. A predesigned Excel worksheet is used to compare the forecast against the observed values and statistical plot were generated. Bias and root mean square error are than calculated based on formulas as follows; a. Bias Bias or mean error indicates whether the forecast system has a tendency to underforecast (Bias <0) or over-forecast (Bias > 0). It does not measure how well the forecast corresponds to the observations. b. Root Mean Square Error Root mean square error (rmse) is the squared root of mean square error. It measures the magnitude of the error, weighted on the squares of the errors. It does not indicate the direction of the error. The RMSE puts greater influence on larger errors than smaller errors, which may be a good thing if large errors are especially undesirable but may also encourage conservative forecasting. Where F i and O i indicate the forecast and observed data respectively N is number of observations. 4

diagrams of 24-hr, 48-hr, 72-hr and 96-hr for

Erb West platform are shown in Figure 2,

a) 24-hr Forecast b) 48-hr Forecast c) 72-hr

7 5. RESULTS a. Statistical evaluation The scatter plot diagrams of 24-hr, 48-hr, 72-hr and 96-hr for WSPD, SWH and WPRD for the entire year 2010 at Erb West platform are shown in Figure 2, Figure 3 and Figure 4 below. a) 24-hr Forecast b) 48-hr Forecast c) 72-hr Forecast d) 96-hr Forecast Figure 2.Scatter plot diagram of forecast and observed WSPD for Erb West platform 5

8 a) 24-hr Forecast b) 48-hr Forecast c) 72-hr Forecast d) 96-hr Forecast Figure 3.Scatter plot diagram of forecast and observed SWH for Erb West platform 6

a) 24-hr Forecast b) 48-hr Forecast c) 72-hr Forecast d) 96-hr Forecast Figure 4.

show positive correlation between the forecast and observed data for WSPD, SWH and WPRD.

are concentrated along the trendline as shown in Figure 3.

9 a) 24-hr Forecast b) 48-hr Forecast c) 72-hr Forecast d) 96-hr Forecast Figure 4.Scatter plot diagram of forecast and observed WPRD for Erb West platform Scatter plot diagrams above show positive correlation between the forecast and observed data for WSPD, SWH and WPRD. The scatter plot diagram for SWH shows good agreement between forecast and observed as majority of data are concentrated along the trendline as shown in Figure 3. The scatter plot diagrams for WSPD (Figure 2) and WPRD (Figure 4) both show larger variations between forecast and observed as majority of data are not concentrated along their trendlines. 7

10 b. Temporal Error Variability The monthly mean bias of 24-hr, 48-hr, 72-hr and 96-hr forecasts for WSPD, SWH and WPRD are shown in Figure 5 below. (a) WSPD (b) SWH (c) WPRD Figure 5.Temporal evolution of bias for (a) WSPD, (b) SWH and (c) WPRD. 8

Figure 5(a) shows that the GFS model has positive bias in all forecasts while predicting WSPD in the months of February, October, November and December.

As for SWH, MMD WAM model recorded positive bias in the months of January, February, October and December, and negative bias in April and July 2013 as shown at Figure 5(b).

11 Figure 5(a) shows that the GFS model has positive bias in all forecasts while predicting WSPD in the months of February, October, November and December. GFS recorded negative bias in May and June in predicting WSPD. As for SWH, MMD WAM model recorded positive bias in the months of January, February, October and December, and negative bias in April and July 2013 as shown at Figure 5(b). The MMD WAM model show negative bias in predicting the WPRD for the entire year 2010 as shown at Figure 5(c). Figure 6 below shows the root mean square errors (rmse) averaged forecast of (a) wind speeds, (b) significant wave heights and (c) wave periods at Erb West site for the entire year of (a) WSPD (b) SWH 9

(c) WPRD Figure 6.Temporal evolution of rmse for (a) wind speeds, (b) significant wave heights and (c) wave periods. The rmse for WSPD is between 3.39 and 5.86 knots as shown at Figure 6(a).

12 (c) WPRD Figure 6.Temporal evolution of rmse for (a) wind speeds, (b) significant wave heights and (c) wave periods. The rmse for WSPD is between 3.39 and 5.86 knots as shown at Figure 6(a). As for SWH, the rmse is between 0.16 and 0.46 meters and recorded higher rmse in the month of March and July and lower in the month of August as shown at Figure 6(b). The rmse for WPRD is between 0.52 and 2.82 seconds and highest in the month of April as shown in Figure 6 (c). Table 1 below shows the monthly root mean square error for WSPD, SWH and WPRD for the Erb West platform. The rsme for WSPD varies between 2.30 knots (24-hr forecast in December) and 5.81 knots (72-hr forecast in March). The average rmse for WSPD for 24-hr forecast is 4.02 knots, and increases towards the 96-hr forecast as shown at Table 1(a) below. For SWH, the rmse ranges between 0.16 meters (72-hr forecast in May) and 0.45 meters (96-hr forecast in July). The average rmse for 24-hr forecast is 0.28 meters, 48-hr and 72-hr forecasts is 0.30 meters respectively, and for 96-hr forecast is 0.32 meters as shown at Table 1(b). As for WPRD, rmse is between 0.86 seconds (96-hr forecast in May) and 2.68 seconds (24-hr forecast in April). The average rmse is between 1.57 and 1.70 seconds as shown at Table 1(c). 10

13 Forecast Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Avg 24-hr Fcst hr Fcst hr Fcst hr Fcst (a) WSPD in knots Forecast Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Avg 24-hr Fcst hr Fcst hr Fcst hr Fcst (b) SWH in meters Forecast Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Avg 24-hr Fcst hr Fcst hr Fcst hr Fcst (c) WPRD in seconds Table 1: Monthly average rmse for (a) WSPD, (b) SWH and (c) WPRD at Erb West platform for the year Maximum value (red) and minimum value (blue). 6. CONCLUSION This verification study by comparing the model data of surface wind speeds, significant wave heights and wave periods against the observations at Erb West platform for the entire year 2010 has reached several conclusions as follows: (1) The average rmse of SWH for 24-hr, 48-hr, 72-hr and 96-hr forecasts at Erb West platform are 0.28, 0.30, 0.30 and 0.32 meters respectively. It is comparable to the T/P altimeter accuracy (smaller than 0.5 m) according to study by Peter C.Chu et al. (2003), which indicates the capability of MMD WAM model in predicting the SWH at Erb West Platform. (2) The rsme for WSPD varies between 2.30 knots (24-hr forecast in December 2010) and 5.81 knots (72-hr forecast in March 2010). The average rmse for WSPD for 24-11

14 hr forecast is 4.02 knots, 48-hr forecast (4.34 knots), 72-hr forecast (4.70 knots) and 96-hr forecast (4.71 knots), higher compare to 2.60 knots by Chung C.L et. al, in their An Empirical Study of Surface Wind Retrievals using the TMI over the South China Sea in the Summer Monsoon Season. This show that the winds input from GFS model are not perform well in predicting WSPD at Erb West platform. (3) The rmse for WPRD is between 0.86 seconds (96-hr forecast in May) and 2.68 seconds (24-hr forecast in April) with average rmse between 1.57 and 1.70 seconds. The bias always under forecast (negative bias) which indicates that the MMD WAM model not perform well in predicting the WPRD at Erb West platform. Acknowledgments. The authors would like to thank Dato Dr Yap Kok Seng, Director General of The Malaysian Meteorological Department (MMD), Mr. Saw Bun Liong, Director of National Weather Forecasting Centre MMD for their encouragement and support, Mr. Muhammad Helmi Abdullah and Mr. Nursalleh K.Chang from the Marine and Oceanography Division MMD for providing the modeled data; colleagues and friends for making this study a success. 12

15 REFERENCES Peter C.Chu, Yiquan Qi, Yuchun Chien, Ping Shi, and Qingwen Mao, 2004: South China Sea Wind-Wave Characteristics. Part I: validation of Wavewatch-III Using TOPEX/Poseidon Data Peter A.E, M Janssen, Bjorn Hansen, and Jean-Raymond Bidlot, 1997: Verification of ECMWF Wave Forecasting System against Buoy and Altimeter Data. Frank Woodcook, and Diana J.M Greenslade, 2006: Consensus of Numerical Forecasts of Significant Wave Heights Callahan, P.S., C.S. Morris, and S.V.Hsiao, 1994: Comparison of TOPEX/POSEIDON and significant wave height distributions to Geosat. J.Geophys.Res.,99, Dobson, E., F. Monaldo, and J. Goldhirsh, 1987: Validation of Geosat altimeter-derived wind speeds and significant wave heights using buoy data, J. Geophys.Res.,92, Tolman, H.L, 1999: User manual and system documentation of WAVEWATCH-III version 1.18, NOAA/NCEP Technical Note 166, pp.110. Ching-Chung Li, and Gin-Rong Liu, 2006: An Empricial Study of Surface Wind Retrievals using the TMI over the South China Sea in the Summer Monsoon Season WMO, Forecast Verification Issues, Methods and FAQ 13

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