First six months quality assessment of HY-2A SCAT wind products using in situ measurements

Transcription

1 Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P DOI: /s First six months quality assessment of HY-2A SCAT wind products using in situ measurements WANG He 1, ZHU Jianhua 1, LIN Mingsen 2, HUANG Xiaoqi 1, ZHAO Yili 1, CHEN Chuntao 1, ZHANG Youguang 2, PENG Hailong 2 1 National Ocean Technology Center, State Oceanic Administration, Tianjin , China 2 National Satellite Ocean Application Service, State Oceanic Administration, Beijing , China Received 24 August 2012; accepted 10 December 2012 The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2013 Abstract The first Chinese microwave ocean environment satellite HY-2A, carrying a Ku-band scatteromenter (SCAT), was successfully launched in August The first quality assessment of HY-2A SCAT wind products is presented through the comparison of the first 6 months operationally released SCAT products with in situ data. The in situ winds from the National Data Buoy Center (NDBC) buoys, R/V Polarstern, Aurora Australis, Roger Revelle and PY30-1 oil platform, were converted to the 10 m equivalent neutral winds. The temporal and spatial differences between the HY-2A SCAT and the in situ observations were limited to less than 5 min and 12.5 km. For HY-2A SCAT wind speed products, the comparison and analysis using the NDBC buoys yield a bias of 0.49 m/s, a root mean square error (RMSE) of 1.3 m/s and an increase negative bias with increasing wind speed observation above 3 m/s. Although less accurate of HY-2A SCAT wind direction at low winds, the RMSE of with a bias of 0.92 is found for wind speeds higher than 3 m/s. These results are found consistent with those from R/Vs and oil platform comparisons. Moreover, the NDBC buoy comparison results also suggest that the accuracy of HY-2A SCAT winds is consistent over the first half year of The encouraging assessment results over the first 6 months show that wind products from HY-2A SCAT will be useful for scientific community. Key words: HY-2A satellite, microwave scatterometer, wind, validation Citation: Wang He, Zhu Jianhua, Lin Mingsen, Huang Xiaoqi, Zhao Yili, Chen Chuntao, Zhang Youguang, Peng Hailong First six months quality assessment of HY-2A SCAT wind products using in situ measurements. Acta Oceanologica Sinica, 32(11): 27-33, doi: /s Introduction For more than a decade, the space-borne scatterometers play a critical role for providing unique global ocean surface wind vector products. Scatterometer-derived winds have been assimilated into atmospheric models for weather and climate studies, and further applied to various scientific applications (Jiang and Song, 2010a; Vogelzang and Stoffelen, 2012). On August 16, 2011, carrying the latest space-borne s- catterometer along with three other microwave sensors, HY- 2A satellite was successfully launched into a polar sunsynchronous orbit of 970 km altitude with an inclination of 99.3 and a local time of equatorial crossing at the descending node near 06:00 am. The HY-2A scatterometer (SCAT) adopts two pencil beams to provide the ocean surface wind vector on more than 90% of the global ocean within 1 d (Jiang et al., 2012). Following a few months of calibration, HY-2A SCAT products have been operationally released by the National Satellite Ocean Application Service (NSOAS) since January Since then, there are three in-orbit scatterometers, including European advanced scatterometer (ASCAT), Chinese HY-2A SCAT and Indian OCEANSAT-2 scatterometer (OSCAT). In this context, the HY-2A SCAT is expected to increase the temporal sampling of scatterometer wind measurements. However, the quality assessment of the HY-2A SCAT wind products is necessary before the data are widely used. Several validation investigations have been carried out for other scatterometer wind products. Quilfen et al. (2001) assessed the accuracy of the ERS scatterometer wind measurements using the buoy winds. For QuikSCAT, the accuracy of the wind products was evaluated through comparison with buoy measurements (Ebuchi et al., 2002; Pickett et al., 2003), research vessel observations (Bourassa et al., 1997; Bourassa et al., 2003) and meteorological station observations in a coastal region (Sánchez et al., 2007). To validate the ASCAT wind data, the scatterometer-derived wind vectors were compared with the outputs from the European Centre for Medium-range Weather Forecasts (ECMWF) model and the buoy observations (Verspeek et al., 2010), and those from QuikSCAT (Bentamy et al., 2008). Mathewa et al. (2012) compared OCEANSAT-2 OSCAT wind products with those from JASON altimeter to assess the quality of the products. This paper presents a first HY-2A SCAT products quality assessment over the first half year of 2012, using various in situ wind observations, including anemometer measurements from moored buoys, research vessels and oil platform. Foundation item: The Marine Public Welfare Project of China under contract No ; the National High-Tech Project of China under contract No. 2008AA09A403; and the fund of State Administration for Science, Technology and Industry for National Defense. *Corresponding author, besmile@263.net 1

2 28 WANG He et al. Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P Data set 2.1 HY-2A SCAT wind data In this study, the NSOAS delivered HY-2A SCAT Level 2B wind products over a period of 6 months from January to June 2012 were used to carry out the first quality assessment (see Table 1 for main parameters of the HY-2A SCAT). For HY-2A S- CAT wind vector retrieval and directional ambiguity removal, the maximum likelihood estimation method and the circle median filter were adopted respectively (Jiang et al., 2012). Table 1. Main parameters of the HY-2A SCAT Frequency/GHz Ku-band Scanning mode conically scanning Swath/km (inner beam) (outer beam) Polarization HH (inner beam); VV (outer beam) Incident angle/( ) 41 (inner beam) 48(outer beam) Wind vector cell size/km Many investigations pointed out that the larger uncertainties of QuikSCAT winds in the outer swath and nadir are due to its pencil beam mechanism (Bourassa et al., 2003; Yuan, 2004; Jiang and Song, 2010b). Similar to QuikSCAT, the Ku-band pencil beam scatterometer HY-2A SCAT suffers the same challenge as well. Therefore, HY-2A SCAT winds in the outer swath (1 4 and of the 74 wind vector cells) and nadir (37 38 cells) were excluded from this study. As HY-2A SCAT operating at the Ku-band, the rain contaminated data also should be removed (Weissman et al., 2002) in the validation. Unfortunately, the rain flag is absent in the current version of HY-2A SCAT Level 2B products. Therefore, the s- canning microwave radiometer on board the same satellite HY- 2A was utilized to discriminate the pixel affected by rain. An investigation of 38 northeast Pacific storm systems (Wentz, 1990) indicates that when the cloud liquid water exceeds 0.18 mm, it looks like rain, thus many studies use this criteria as an indicator of rain (Mears et al., 2001; Meissner and Wentz, 2005). Therefore, the cloud liquid water from HY-2A radiometer greater than 0.18 mm is identified to be rain, and then the corresponding HY-2A SCAT wind products are discarded. 2.2 In situ wind data Widely spatial distributed in situ wind observations from various platforms were used, including measurements of moored buoy data, oil platform wind data and ship-borne data. The geographical locations and information of these in situ observations are shown in Fig. 1 and Table 2. The details of the data used are as follows. Fig.1. Locations of the in situ observations used in the validation. 49 moored buoys and PY30-1 oil platform are marked with dots and pentagram, respectively. The cruise track of R/V Polarstern, Aurora Australis and Roger Revelle are plotted with blue, green and yellow lines, respectively. Table 2. Summary of in situ observations Location Anemometer Wind data sampling interval Time height/m interval NDBC moored buoy off United States coasts and Hawaii Islands 10 or 5 10 min January to June,2012 PY30-1 oil platform South China Sea s January to April, 2012 R/V Polarstern Atlantic min January to May,2012 R/V Aurora Australis Southern Ocean 30 1 min January to April,2012 R/V Roger Revelle western Pacific, Indian Ocean 17 1 min January to June, Moored buoy wind observations Continuous winds data (10 min averaged) have been collected from 49 moored buoys operated by the National Data Buoy Centre (NDBC) from January to June As shown in Fig. 1, all the selected buoys are far from the land more than 50 km Research vessel wind observations The ship-borne wind data used for the present study were collected from three research vessels, of which ship cruise tracks in different ocean basins are shown in Fig. 1.

3 WANG He et al. Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P The German R/V Polarstern obtained wind speed and direction observations in Atlantic ocean during three cruises (ANT-XXVIII/3, 4, and 5) conducted from January to May In situ wind data in Southern Ocean were collected from January to April 2012 from the Australian R/V Aurora Australis during the cruises of V3, 4, 5 and 6. In the western Pacific and Indian Ocean, wind measurements were obtained from the cruises of United States R/V Roger Revelle during the period from January to June, All the wind data from these research vessels have been calculated to the true winds (earth relative winds) and quality controlled to avoid the flow distortion. Research vessel measurements also include surface meteorological parameters, such as air temperature, sea surface temperature, dew point temperature, and sea surface pressure, which will be used in the 10 m equivalent neural wind conversion Oil platform wind observations The PY30-1 oil platform is located in the South China Sea ( N, E), 250 km away from the nearest coastline (see Fig. 1). As shown in Fig. 2, an anemometer is equipped at well exposed location of the oil platform top (101 m above mean sea level). In addition to the wind, sea surface temperature and meteorological measurements (air temperature, air pressure, relative humidity) were collected from the CTD and the meteorological sensor of the oil platform, respectively. Fig.2. Picture of PY30-1 platform. The location of the anemometer is circled in red m equivalent neutral winds conversion Because the wind products of HY-2A scatterometer are e- quivalent neutral wind vectors at 10 m height above the sea surface, all the in situ measurements, including the data from buoys, oil platform and research vessels, obtained at different heights (as listed in Table 2) must be converted to the 10 m equivalent neutral winds in order to be comparable. In this s- tudy, the conversion was performed using the coupled oceanatmosphere response experiment (COARE) bulk algorithm (version 3.0) developed by Fairall et al. (2003). 2.4 Collocation procedure For validation purpose, the HY-2A SCAT data and the in situ observations were collocated in time and space. The spatial interval was limited to less than 12.5 km, half of the HY-2A SCAT cell width. The observations from the NDBC buoys and R/V Polarstern are available every 10 min. For higher temporal resolution in situ observations, including from PY30-1 oil platform, R/V Aurora Australis and Roger Revelle, 10 min measurements, centered at the closest time to HY-2A SCAT acquisition, were averaged. Thus, the maximum time difference between HY-2A SCAT and in situ measurements is 5 min. 3 Comparison and analysis 3.1 Buoy comparison Figure 3 shows the overall comparison results of HY-2A S- CAT products and the NDBC moored buoy observations. For wind speed, a good agreement is shown in Fig. 3a, with a small bias of 0.49 m/s, and a root mean square error (RMSE) of 1.3 m/s, with respect to the NDBC buoy measurements. In the comparison of the wind direction, as is shown in Fig. 3b, the RMSE as large as with a bias of 1.35 is present for the whole wind speed range. If only HY-2A SCAT data with the buoy wind speed higher than 3 m/s were used in the comparison, the RMSE is reduced to with a bias of 0.92, as the scatter plot shown in Fig. 3c. This result indicates that the mission requirement for HY-2A SCAT wind direction products retrieval (less than 20 ), is almost satisfied in the wind speed range of 3 m/s above, although a poor performance of the wind direction products at the low wind speed is found. The dependency of HY-2A SCAT products accuracy was Fig.3. Scatter plots of HY-2A SCAT winds versus NDBC moored buoy measurements for wind speed comparison (a), wind direction comparison with all wind speed range (b) and wind direction comparison with wind speed greater than 3 m/s (c), respectively.

4 30 WANG He et al. Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P analyzed using the collocations of HY-2A and NDBC buoys. HY- 2A SCAT minus buoy wind speed difference and standard deviation as a function of buoy wind speed over a range from 1 to 20 m/s are shown in Fig. 4a. In general, a negative bias is clearly found, except for an overestimation at very low wind speeds (blow 3 m/s). Above 3 m/s, a negative bias tends to increase with the wind speed observation. Figure 4b illustrates the dependency of wind direction residual on the buoy wind speed. The large standard deviation at low wind decreases to about 20 with the wind speed larger than 3 m/s. It is indicated that the wind direction at low winds is less accurate for HY-2A SCAT, consistent with the result of s- catter plots mentioned above (see Figs 3b and c). In order to investigate the temporal variation of HY-2A SCAT wind products accuracy, statistics were calculated for 6 months by every 10 d on the basis of HY-2A-buoy collocations. In Fig. 5, the mean bias (HY-2A minus buoy) and standard deviation for the wind speed (Fig. 5a) and the wind direction (Fig. 5b) are plotted versus time for the first half year of 2012, with the histograms showing numbers of data. Owing to the absence of HY-2A SCAT products during the first 2 weeks of March, a gap of the seventh 10 d can be found in Fig. 5. It is shown that both the bias and standard deviation of HY-2A SCAT wind speed and wind direction stay relatively constant over the period of 6 months. This results suggest that the accuracy of HY-2A SCAT winds is consistent over the first half year of Fig.4. The bias (HY-2A SCAT minus buoy) and the standard deviation (shown by error bars) of the wind speed (a) and direction(b) for each 1 m/s buoy wind speed bin. Fig.5. The bias (HY-2A SCAT minus buoy) and the standard deviation (shown by error bars) of the wind speed (a) and direction(b) for each 10 d bin. 3.2 Research vessels and oil platform comparison The large number of moored buoys allow the robust statistical comparison and error analysis on the wind speed and the temporal dependency, as carried out in the above subsection. However, the distribution of the NDBC moored buoys is limited to the U S coast. In addition to the observations from these moored buoys, the in situ measurements from research vessels and oil platform can be used to extend the quality assessment to a spatial coverage other than NDBC buoys. In this subsection, HY-2A SCAT winds are compared with research vessels and oil platform, in order to assess the results obtained from buoy and HY-2A SCAT comparison. Figures 6 and 7 illustrate the comparison of HY-2A SCAT winds and observations from three research vessels and PY30-1 oil platform for both wind speed and wind direction. In these plots, only HY-2A SCAT data with a in situ wind speed higher than 3 m/s were used in the wind direction comparison. The statistical comparison is made using the in situ observations, including NDBC buoys, research vessels and oil platform, and results are listed together in Table 3. For R/V Polarstern and Aurora Australis, the results are shown in Figs 6a,b,c and d. For the wind direction, the HY-2A SCAT products are in good agreement with observations from these R/Vs. In terms of the HY-2A SCAT wind speed, the bias and RMSE respect to R/V Polarstern are 0.98 and 1.60 m/s, and respect to R/V Aurora Australis are 1.34 and 1.72 m/s, re-

5 WANG He et al. Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P spectively. The wind speed comparison result from these two ships shows more significant underestimation than the NDBC buoy assessment. This may be resulted from the different spatial distributions of the two collocated data sets. As shown in Fig. 1, many in situ data from these two vessels were collected in the Southern Ocean, where the strongest wind fields on the ocean surface exist. Indeed, the mean wind speed from ship in this study is 9.49 and 9.42 m/s for R/V Polarstern and Aurora Australis, respectively, comparing with 7.49 m/s for the NDBC buoys. Therefore, the comparison results from these two ships, are consistent with the error analysis on HY-2A SCAT winds using buoy data. Figure 7 shows the comparison results of the HY-2A SCAT winds and the in situ data from R/V Roger Revelle and the PY30-1 oil platform, respectively. These in situ measurements were obtained in the Indian Ocean, the western Pacific and the South Table 3. Summary of the comparison results using the in situ observations In situ Location Mean wind HY-2A SCAT wind speed HY-2A SCAT wind direction speed/m s 1 bias/m s 1 RMSE/m s 1 bias/( ) RMSE/( ) NDBC buoy United States coasts and Hawaii Islands R/V Polarstern Atlantic R/V Aurora Australis Southern Ocean R/V Roger Revelle western Pacific Indian Ocean PY30-1 oil platform South China Sea Note: only HY-2A SCAT data with in situ wind speed higher than 3 m/s were used in the wind direction comparison. Fig.6. Scatter plots of HY-2A SCAT wind speed and wind direction versus in situ observations, from R/V Polarstern (a, b) and R/V Aurora Australis (c, d), respectively.

6 32 WANG He et al. Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P Fig.7. Scatter plots of HY-2A SCAT wind speed and wind direction versus in situ observations, from R/V Roger Revelle (a, b) and PY30-1 oil platform (c, d), respectively. China Sea with a mean wind speed of about 6 m/s. The lower wind speeds result in less accurate of the HY-2A SCAT wind direction, with a RMSE of and for R/V Roger Revelle and oil platform, comparing with the assessment results using the NDBC buoys (RMSE of ), R/V Polarstern (RMSE of ) and Aurora Australis observations (RMSE of ). And in these lower wind cases, the underestimation of the HY-2 wind speed is not as pronounced as that shown in the comparison with R/V Polarstern and Aurora Australis, with a bias of 0.80 and 0.51 m/s respect to R/V Roger Revelle and the PY30-1 oil platform, respectively. 4 Conclusions In this study, the first accuracy assessment of the ocean surface wind vector from the SCAT on the recently launched HY-2A satellite has been carried out through the comparison with the in situ observations from moored buoys, research vessels and oil platform over the period of the first half year of A HY-2A SCAT wind speed bias of 0.49 m/s, and a RMSE of 1.3 m/s are found in the comparison with the NDBC moored buoys. In addition, an increase negative bias with increasing wind speed observation above 3m/s is shown, in the dependency analysis of wind speed residuals using the SCAT buoy collocation. For wind speed higher than 3 m/s, the HY-2 SCAT wind direction RMSE of with a bias of 0.92 in respect to the buoy winds is presented, although less accurate at low winds. The quality assessment results of wind speed and direction have also been confirmed through comparisons with other in situ measurements, including from R/V Polarstern, Aurora Australis, Roger Revelle and PY30-1 oil platform. Moreover, the temporal stability of HY-2A SCAT wind products accuracy over the period of 6 months is demonstrated through every 10 d comparison with buoys. The first 6 months assessment results show that the wind products from HY-2A SCAT may meet the requirements of scientific community. Although some improvements are needed

7 WANG He et al. Acta Oceanol. Sin., 2013, Vol. 32, No. 11, P to enhance the quality, it can be concluded that HY-2A SCAT products have been a useful data set of the global ocean surface winds for weather prediction models and other uses. Ac k now l e d g e m e n t s The authors are thankful for free access to the in situ observations from the buoy provided by the National Data Buoy Center. References Bentamy A, Croize-Fillon D, Perigaud C Characterization of AS- CAT measurements based on buoy and QuikSCAT wind vector observations. Ocean Science, 4: Bourassa M A, Freilich M H, Legler D M, et al Wind observations from new satellite and research vessels agree. EOS Transaction of American Geophysical Union, 78: 597 Bourassa M A, Legler D M, O Brien J J, et al SeaWinds validation with research vessels. Journal of Geophysical Research, 108: 3019, doi: /2001jc Ebuchi N, Graber H C, Caruso M J Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data. Journal of Atmospheric and Oceanic Technology, 19: Fairall C W, Bradley E F, Hare J E, et al Bulk parameterization of air sea fluxes: updates and verification for the COARE algorithm. Journal of Climate, 16: Jiang Xingwei, Lin Mingsen, Liu Jianqiang, et al The HY-2 satellite and its preliminary assessment. International Journal of Digital Earth, 5: Jiang Xingwei, Song Qingtao. 2010a. Satellite microwave measurements of the global oceans and future missions. Science and Technology Review (in Chinese), 28: Jiang Xingwei, Song Qingtao. 2010b. A climatology of sea surface wind speed and wind stress fields constructed from scatterometer observations. Acta Oceanologica Sinica (in Chinese), 32: Mathewa T, Chakraborty A, Sarkar A, et al Comparison of oceanic winds measured by space-borne scatterometers and altimeters. Remote Sensing Letters, 3: Mears C A, Smith D K,Wentz F J Comparison of SSM/I and buoy-measured wind speeds from 1987 to Journal of Geophysical Research,106: Meissner T, Wentz F J Ocean retrievals for WindSat: radiative transfer model, algorithm, validation. Proceedings of the 9th Specialist Meeting on Microwave Radiometry and Remote Sensing Applications, San Juan, Puerto Rico: IEEE Pickett M H, Tang W Q, Rosenfeld L K, et al QuikSCAT satellite comparisons with nearshore buoy wind data off the U.S. west coast. Journal of Atmospheric and Oceanic Technology, 19: Quilfen Y, Chapron B, Vandemark D The ERS scatterometer wind measurement accuracy: evidence of seasonal and regional biases. Journal of Atmospheric and Oceanic Technology, 18: Sánchez R F, Relvas P, Pires H O Comparisons of ocean scatterometer and anemometer winds off the southwestern Iberian Peninsula. Continental Shelf Research, 27: Verspeek J, Stoffelen Ad, Portabella M, et al Validation and calibration of ASCAT using CMOD5.n. IEEE Transactions on Geoscience and Remote Sensing, 48: Vogelzang J, Stoffelen Ad Scatterometer wind vector products for application in meteorology and oceanography. Journal of Sea Research, 73: doi: /j.seares Weissman D E, Bourassa M A, Tongue J Effects of rain rate and wind magnitude on SeaWinds scatterometer wind speed errors. Journal of Atmospheric and Oceanic Technology, 19: Wentz F J SBIR phase II report: West coast storm forecasting with SSM/I. Santa Rosa, Remote Sensing Systems, 378 Yuan Xiaojun High wind evaluation in the Southern Ocean. Journal of Geophysical Research, 109: D13101, doi: / 2003JD00417