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Assessment and inter-comparison of five GHRSST products in the coastal and shelf sea around China

Assessment and inter-comparison of five GHRSST products in the coastal and shelf sea around China. Jiping Xie 1,3 , Jiang Zhu 1 , and Yan Li 2,3. 1. Institute of Atmospheric Physics, CAS 2. National Marine Environmental Forecasting Center, Beijing

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Assessment and inter-comparison of five GHRSST products in the coastal and shelf sea around China

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  1. Assessment and inter-comparison of five GHRSST products in the coastal and shelf sea around China Jiping Xie1,3, Jiang Zhu1, and Yan Li2,3 1. Institute of Atmospheric Physics, CAS 2. National Marine Environmental Forecasting Center, Beijing 3. Graduate School of the Chinese Academy of Sciences Melbourne, Australia, May 2007

  2. Outline • Background • Data Processing • Inter-comparison GHRSST products • Assessment by in situ observations • Conclusions

  3. GRHSST L4 Products: MWOISST (RSS ), NGSST (UT, Japan), MGDSST (JMA),OSTIA (NCOF), FSTIA (FNMOC) Annual SST: (2005.10~2006.9)

  4. However, we notice there are some … … MGDSST OSTIA

  5. Questions • How about the differences and errors of the five GHRSST products in the coastal and shelf sea around China? • How to improve the GHRSST products as a major input for data assimilation in this region? • Can we use the ensemble mean method to improve the presently GHRSST products?

  6. 2. Data Processing • GHRSST L4 Products Cover: 116-135ºE, 20~42ºN; period: 2005.10~2006.9

  7. DDGR: Jun 2006 • In Situ Observations Drifting buoy and Ship reports are collected by Near-Goos (http://near-goos1.jodc.go.jp) from GTS. I. Pre-process • Excluding the reports with invalid ship signal. • Excluding the redundant reports. • Position check by tracking consistency method as Kent and Challenor(2006). Night SST : SHIP ~ 3167; BUOY ~ 7284

  8. II. Quality Control • Comparing the monthly SST for a ship or buoy with climatology, if outside of 3 standard deviation, the observations in this month will be rejected. • Excluding any record outside of 4.5 standard deviation referring to monthly climatology from GDEM-V3.0. • Consistency checking by the EMSST linear regression with 99% confidence level. 14.3% 6.2% SHIP : 2715 BUOY : 6835

  9. Num: 115 426 379 1795 Num: 120 198 573 5944 Distributions of in situ daily SST observations through data quality control Depth (m) : •<40 •40~80 •80~200 •>200

  10. 3. Inter-comparison of GRHSST Difference of annual SST referring to EMSST during the period of 2005.10~2006.9 a.) MWOISST (b.) NGSST (c.) MGDSST (d.) OSTIA (e.) FSTIA

  11. Evaluate the difference about the five products: Spatial distribution of the annual difference spread relative to EMSST (left) and the averaged difference spread as a function of depths (right). Note: if the sample is over 40 in a depth interval, a red circle can be shown.

  12. 4. Assessment by in situ observations Table 2. Comparison of Bias and RMSE of the different SST products referring to buoy observations (ºC)

  13. Comparison of bias and RMSE of SST products relative to buoy and ship observations in different depth interval. The histogram denotes the bias, and the error bar denotes the corresponding RMSE.

  14. Correct Increment: Depth < 40 m

  15. Bias (ºC) OSTIA/New 0.2/-0.01 -0.03/-0.04 -0.02/0.02 -0.05/0.0 Bias (ºC) FSTIA/New 0.4/0.07 0.07/-0.04 0.08/0.02 0.06/0.0 Comparison of Bias and RMSE through the Correction Comparison of bias and RMSE of SST products through correction according to the depth scale. The histogram denotes the bias, and the error bar denotes the corresponding RMSE.

  16. Comparison of Bias and RMSE through the Correction Table 3. Changes of Bias and RMSE through correction to Buoy SST (ºC) Table 4. Changes of Bias and RMSE through correction to Ship SST (ºC) Referring to buoy SST, the bias can be decreased an order, but the RMSE can be decreased by 1% (OSTIA) and 4% (FSTIA) of RMSE.

  17. Mean: (ºC) 1.6 1.0 0.8 -0.2 Mean: (ºC) 3.5 3.3 2.3 2.2 Validation of the corrected SSTs by night SST Observations of 12 Coastal Stations Comparison of bias and RMSE of OSTIA and FSTIA by exponent correction relative to costal station observations. On average, the RMSE can be decreased about 5% and 3%, respectively to OSTIA and FSTIA.

  18. 7415 7416 7424

  19. 5. Conclusions Looking for a major data source to feed our data assimilation system for preoperational ocean forecast, we investigate the five GHRSST Level 4 products in the coastal and shelf sea around China. The five GHRSST products are compared to each other and to the in situ SST observations in the period of 2005.10~2006.9. Some efforts to correct the bias near coastal regions are made. The main results are: • These products are agreed with very well when water depth is larger than 80m. However, near the coast around China, large differences exist. For example, as the depth is less than 40m, the annual mean spread of them is nearly to 0.9ºC.

  20. Comparing to in situ observations, most of them are excellent for reasonable bias and RMSE. Especially the RMSE of OSTIA and FSTIA (reference to buoy SST observations) are about 0.3ºC. However near the coast, i.e, the depth is less than 40m, the warm bias (>0.2ºC) and the considerable RMSE (>0.6ºC) are prevalent in the five products. • A bias correction scheme that uses an exponent function of depth is applied to two products (OSTIA and FSTIA). The correction can reduce bias effectively, however, the RMSE doesn’t reduced so effectively. • The current GHRSST L4 products, especially some of them, can be safely used as a major input of data assimilation system in the shelf sea around China. However, near the coastline where depth is less than 40m, they are not ready to be assimilated. It is necessary to make further correction or improvement.

  21. Thank you !

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