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

被引:1
|
作者
Luo, Yulan [1 ,2 ,3 ]
Liu, Lin [1 ,2 ,3 ]
Paul, Oloo [4 ]
Philip, Sagero [4 ,5 ]
Li, Kuiping [1 ,2 ]
Yang, Yang [1 ,2 ]
Su, Qinglei [1 ,2 ]
Li, Qiuchi [1 ,2 ]
Miao, Zichen [1 ,2 ]
机构
[1] Minist Nat Resources, Inst Oceanog 1, Pilot Natl Lab Marine Sci & Technol, Qingdao 266061, Peoples R China
[2] Pilot Natl Lab Marine Sci & Technol, Lab Reg Oceanog & Numer Modeling, Qingdao 266061, Peoples R China
[3] Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 510275, Peoples R China
[4] Kenya Meteorol Dept, Nairobi 30259, Kenya
[5] Univ South Pacific, Dept Geog Earth Sci & Environm, Bag Suva 17257, Fiji
基金
中国国家自然科学基金;
关键词
Bailong buoy; reanalysis; Indian Ocean; sea level pressure; surface wind; CLIMATE; PRECIPITATION; TRENDS; WIND;
D O I
10.1007/s11802-023-5410-2
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
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.
引用
收藏
页码:863 / 873
页数:11
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