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Assessment of Atmospheric Reanalysis Data Based on Buoy Observations over the Tropical Western Indian Ocean in 2019

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Abstract

Atmospheric reanalysis data are an important data source for studying weather and climate systems. The sea surface wind and sea level pressure observations measured from a real-time buoy system deployed in Kenya’s offshore area in 2019 conducted jointly by Chinese and Kenyan scientists were used to evaluate the performance of the major high-frequency atmospheric reanalysis products in the western Indian Ocean region. Compared with observations, the sea level pressure field could be accurately simulated using the atmospheric reanalysis data. However, significant discrepancies existed between the surface wind reanalysis data, especially between meridional wind and the observational data. Most of the data provide a complete understanding of sea level pressure, except for the Japanese 55-year Reanalysis data, which hold a significant system bias. The Modern-Era Reanalysis for Research and Applications, Version-2, provides an improved description of all datasets. All the reanalysis datasets for zonal wind underestimate the strength during the study period. Among reanalysis data, NCEP-DOE Atmospheric Model Intercomparison Project reanalysis data presents an inaccurate description due to the worst correlation with the observations. For meridional wind, most reanalysis datasets underestimate the variance, while the European Centre for Medium-Range Weather Forecasts Atmospheric Composition Reanalysis 4 has a larger variance than the observations. In addition to the original data comparison, the diurnal variability of sea level pressure and surface wind are also assessed, and the result indicates that the diurnal variations have a significant gap between observation and reanalysis data. This study indicates that the current high-frequency reanalysis data still have disadvantages when describing the atmospheric parameters in the Western Indian Ocean region.

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References

  • Agarwal, A., Venugopal, V., and Harrison, G. P., 2013. The assessment of extreme wave analysis methods applied to potential marine energy sites using numerical model data. Renewable and Sustainable Energy Reviews, 27 (6): 244–257.

    Article  Google Scholar 

  • Bengtsson, L., and Shukla, J., 1988. Integration of space and in situ observations to study global climate change. Bulletin of the American Meteorological Society, 69 (10): 1130–1143.

    Article  Google Scholar 

  • Bromirski, P. D., Cayan, D. R., and Flick, R. E., 2005. Wave spectral energy variability in the Northeast Pacific. Journal of Geophysical Research: Oceans, 110 (C3): 1–15.

    Article  Google Scholar 

  • Campos, R. M., and Guedes Soares, C., 2016. Comparison of HIPOCAS and ERA wind and wave reanalyses in the North Atlantic Ocean. Journal of Ocean Engineering and Marine Energy, 112: 320–334.

    Article  Google Scholar 

  • Cardone, V. J., Callahan, B. T., Chen, H., Cox, A., Morronr, M., and Swail, V., 2015. Global distribution and risk to ship** of very extreme sea states (VESS). International Journal of Climatology, 35 (1): 69–84.

    Article  Google Scholar 

  • Checchi, F., and Robinson, W. C., 2013. Mortality among populations of southern and central Somalia affected by severe food insecurity and famine during 2010–2012. FAO and FEWS NET, Rome, Washington, 87pp.

    Google Scholar 

  • Chiang, J., Kong, W., Wu, C. H., and Battisti, D., 2020. Origins of East Asian summer monsoon seasonality. Journal of Climate, 33 (18): 7945–7965.

    Article  Google Scholar 

  • Conrad, L. I., 1986. The history of famine and epidemics in Ethiopia prior to the twentieth century. Medical History, 30 (4): 481–482.

    Article  Google Scholar 

  • Cullather, R., and Bosilovich, M., 2017. Climate data guide–Modern era retrospective analysis for research and applications, version 2 (MERRA-2). NTRS-NASA Technical Reports Server, Document ID: 20170010657.

  • Dai, A. G., and Wang, J. H., 2016. Diurnal and semidiurnal tides in global surface pressure fields. Journal of Atmospheric Sciences, 56: 3874–3891.

    Article  Google Scholar 

  • Freitag, H. P., Ning, C., Berk, P., Dougherty, D. M., Marshall, R. F., Strick, J. M., et al., 2016. ATLAS, T-Flex, BaiLong meteorological sensor comparison test report. NOAA Technical Memorandum OAR PMEL, NOAA/Pacific Marine Environmental Laboratory, Seattle, WA, 1–20.

    Google Scholar 

  • Gemmrich, J., Thomas, B., and Bouchard, R., 2011. Observational changes and trends in Northeast Pacific wave records. Geophysical Research Letters, 38 (22): L22601–L22605.

    Article  Google Scholar 

  • Gilkes, P., 1994. Evil days: 30 years of war and famine in Ethiopia. Disasters, 18(1): 93.

    Google Scholar 

  • Guedes Soares, C., and Scotto, M., 2001. Modelling uncertainty in long-term predictions of significant wave heigh. Ocean Engineering, 28 (3): 329–342.

    Article  Google Scholar 

  • Harada, Y., Kamahori, H., Kobayashi, C., Endo, H., Kobayashi, S., Ota, Y., et al., 2016. The JRA-55 reanalysis: Representation of atmospheric circulation and climate variability. Journal of the Meteorological Society of Japan, 94 (3): 269–302.

    Google Scholar 

  • Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., et al., 2020. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146 (730): 1999–2049.

    Article  Google Scholar 

  • Hodges, K. I., Hoskins, B. J., Boyle, J., and Thorncroft, C., 2003. A comparison of recent reanalysis datasets using objective feature tracking: Storm tracks and tropical easterly waves. Monthly Weather Review, 131: 2012–2037.

    Article  Google Scholar 

  • Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A. M., et al., 2019. The CAMS reanalysis of atmospheric composition. Atmospheric Chemistry and Physics, 19 (6): 3515–3556.

    Article  Google Scholar 

  • Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., et al., 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77 (3): 473–472.

    Article  Google Scholar 

  • Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S. K., Hnilo, J. J., Fiorino, M., et al., 2002. NCEP-DOE AMIP-II reanalysis (R-2). Bulletin of the American Meteorological Society, 83 (11): 1631–1643.

    Article  Google Scholar 

  • Kew, S. F., Philip, S. Y., Hauser, M., Hobbins, M., Wanders, N., Oldenborgh, G., et al., 2019. Impact of precipitation and increasing temperatures on drought in eastern Africa. Earth System Dynamics, 12: 17–35.

    Article  Google Scholar 

  • Kim, H., Lee, M. I., Kim, S., Lim, Y. K., Schubert, S. D., and Molod, A. M., 2017. Representation of tropical cyclones by the modern-era retrospective analysis for research and applications version 2. Asia-Pacific Journal of Atmospheric Sciences, 57 (1): 35–49.

    Article  Google Scholar 

  • Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., et al., 2015. The JRA-55 reanalysis: General specifications and basic characteristics. Journal of the Meteorological Society of Japan, 93 (1): 5–48.

    Google Scholar 

  • Li, J. Y., Wen, M., Wang, Z. Y., and Hu, Y., 2020. Relations between the quasi-biweekly oscillation over the East Asian monsoon region and the East Asian tropical monsoon depressions. International Journal of Climatology, 41 (2): 878–895.

    Article  Google Scholar 

  • Lyon, B., 2004. The strength of El Niño and the spatial extent of tropical drought. Geophysical Research Letters, 31 (21): 1–4.

    Article  Google Scholar 

  • Masatake, E. H., Jun, I., Klaus, D., and Vasilli, K., 2021. Near-tropopause bias in the Russian radiosonde-observed air temperature during the YOPP special observing periods in 2018. Polar Science, 27: 100601.

    Article  Google Scholar 

  • Portilla, J., Sosa, J., and Cavaleri, L., 2013. Wave energy resources: Wave climate and exploitation. Renewable Energy: An International Journal, 57: 594–605.

    Article  Google Scholar 

  • Simmons, A. J., Willett, K. M., Jones, P. D., Thorne, P. W., and Dee, D. P., 2010. Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets. Journal of Geophysical Research: Atmospheres, 115 (D1): 1–13.

    Article  Google Scholar 

  • Song, X. Z., Ning, C. L., Duan, Y. L., Wang, H. W., Li, C., Yang, Y., et al., 2021. Observed extreme air-sea heat flux variations during three tropical cyclones in the tropical southeastern Indian Ocean. Journal of Climatology, 34 (9): 3683–3705.

    Article  Google Scholar 

  • Stopa, J. E., and Cheung, K. F., 2014. Intercomparison of wind and wave data from the ECMWF reanalysis interim and the NCEP climate forecast system reanalysis. Ocean Modelling, 75: 65–83.

    Article  Google Scholar 

  • Taylor, K. E., 2001. Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research, 106 (D7): 7183–7192.

    Article  Google Scholar 

  • Trenberth, K. E., and Olson, J. G., 1989. Temperature trends at the south pole and McMurdo sound. Journal of Climatology, 2 (10): 1196–1206.

    Article  Google Scholar 

  • Wang, L., 1999. East Asian monsoon climate during the Late Pleistocene: High-resolution sediment records from the South China Sea. Marine Geology, 156 (1–4): 245–284.

    Article  Google Scholar 

  • Wang, S. H., Zhao, Y. D., Yin, X. Q., and Qiao, F. L., 2018. Current status of global ocean reanalysis datasets. Advances in Earth Science, 33 (8): 794–807 (in Chinese with English abstract).

    Google Scholar 

  • Wang, X., Zhang, R. W., Huang, J., Zeng, L. L., and Huang, F., 2017. Biases of five latent heat flux products and their impacts on mixed-layer temperature estimates in the South China Sea. Journal of Geophysical Research: Oceans, 122 (6): 5088–5104.

    Article  Google Scholar 

  • Xu, L., **e, S. P., and Liu, Q., 2013. Fast and slow responses of the North Pacific mode water and Subtropical Countercurrent to global warming. Journal of Ocean University of China, 12 (2): 216–221.

    Article  Google Scholar 

  • Xu, P., Feng, J., and Wen, C., 2016. Asymmetric role of ENSO in the link between the East Asian winter monsoon and the following summer monsoon. Journal of Geophysical Research: Atmospheres, 126 (4): 831–840.

    Google Scholar 

  • Yang, W. C., Seager, R., Cane, M. A., and Lyon, B., 2014. The East African long rains in observations and models. Journal of Climatology, 27 (19): 7185–7202.

    Article  Google Scholar 

  • Zhang, R., Huang, J., Wang, X., Zhang, J. A., and Huang, F., 2016. Effects of precipitation on sonic anemometer measurements of turbulent fluxes in the atmospheric surface layer. Journal of Ocean University of China, 15 (3): 389–398.

    Article  Google Scholar 

  • Zhou, F., Zhang, R., Shi, R., Chen, J., He, Y. K., Wang, D. X., et al., 2018. Evaluation of OAFlux datasets based on in situ air-sea flux tower observations over the Yongxing Islands in 2016. Atmospheric Measurement Techniques, 11 (11): 6091–6106.

    Article  Google Scholar 

  • Zhou, Z. Q., **e, S. P., Zheng, X. T., and Liu, Q. Y., 2013. Indian Ocean dipole response to global warming: A multi-member study with CCSM4. Journal of Ocean University of China, 12 (2): 209–215.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the Global Change and Air-Sea Interaction Program (No. GASI-04-QYQH-03), the Taishan Scholars Program of Shandong Province (No. tsqn 201909165), the National Natural Science Foundation of China (No. 41876028), the Global Change and Air-Sea Interaction Program (No. GASI-01-WIND-STwin), the Shandong Science and Technology Foundation (No. 2013GRC 31504), and the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) (No. 2022QNLM010103-3).

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Authors and Affiliations

  1. First Institute of Oceanography, Ministry of Natural Resources and Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology, Qingdao, 266061, China

    Yulan Luo, Lin Liu, Kui** Li, Yang Yang, Qinglei Su, Qiuchi Li & Zichen Miao

  2. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 510275, China

    Yulan Luo & Lin Liu

  3. Kenya Meteorological Department, Nairobi, 30259, Kenya

    Oloo Paul & Sagero Philip

  4. Department of Geography, Earth Science and Environment, The University of the South Pacific, Bag Suva, 17257, Fiji

    Sagero Philip

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  1. Yulan Luo
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  2. Lin Liu
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  3. Oloo Paul
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  4. Sagero Philip
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  5. Kui** Li
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  6. Yang Yang
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  7. Qinglei Su
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  8. Qiuchi Li
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  9. Zichen Miao
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Correspondence to Lin Liu.

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Luo, Y., Liu, L., Paul, O. et al. Assessment of Atmospheric Reanalysis Data Based on Buoy Observations over the Tropical Western Indian Ocean in 2019. J. Ocean Univ. China 22, 863–873 (2023). https://doi.org/10.1007/s11802-023-5410-2

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  • DOI: https://doi.org/10.1007/s11802-023-5410-2

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