基于志愿观测船数据对ERA5海面气温气压的适用性分析

Applicability Analysis of ERA5 Sea Surface Temperature and Pressure Based on Voluntary Observing Ship Data

关键词:  ERA5  志愿观测船  气温  气压  北大西洋  西太平洋  印度洋

Key words:  ERA5  volunteer observing ship（VOS）  air temperature  pressure  North Atlantic  Western Pacific  Indian Ocean

摘要:

本研究基于2021—2023年中国气象局气象大数据云平台提供的志愿观测船（VOS）数据，全面评估了ERA5再分析资料中2m气温和2m气压要素在全球海域，特别是西太平洋、北大西洋和印度洋三大洋区的适用性。评估过程中采用了相关系数(CC)、相对偏差(RB)、均方根误差(RMSE)、平均误差(ME)和平均绝对误差(MAE)等定量统计指标，以确保评估结果的准确性和可靠性。结果显示，ERA5气温和气压数据与VOS观测数据在整体上保持一致，但存在显著的误差。ERA5气温数据普遍低于VOS观测数据，且在不同季节表现出不同的误差特征。冬季气温数据质量最佳，CC值高达0.99，但西太平洋地区存在高估现象；夏季气温数据质量稍逊，离散程度较大。对于气压数据，夏季CC值最低，平均仅为0.68，且在印度洋的春、秋和冬季，CC值也相对较低，RMSE和MAE明显偏大。此外，气温数据还表现出明显的日变化特征，而气压数据则呈现出较为明显的区域性特征。虽然ERA5气温和气压数据在全球海域的整体上与VOS观测数据一致，但在具体数值上存在显著误差，且这些误差在不同季节、不同海域以及日变化上表现出不同的特征。因此，在使用ERA5数据进行海洋气象和海洋环流研究时，需要充分考虑其适用性和局限性，并进行必要的验证和校正，以确保研究结果的准确性和可靠性。

Abstract:

This study comprehensively evaluates the applicability of the 2-meter temperature and 2-meter pressure elements in the ERA5 reanalysis data over global oceans, particularly in the three major oceanic regions of the Western Pacific, North Atlantic, and Indian Ocean, based on Volunteer Observing Ship (VOS) data provided by the China Meteorological Administration's meteorological big data cloud platform from 2021 to 2023. Quantitative statistical indicators such as the correlation coefficient (CC), relative bias (RB), root mean square error (RMSE), mean error (ME), and mean absolute error (MAE) were employed in the evaluation process to ensure the accuracy and reliability of the results. The findings reveal that, while the overall trends of the ERA5 temperature and pressure data align with the VOS observations, significant errors exist. The ERA5 temperature data are generally lower than the VOS observations and exhibit different error characteristics across different seasons. Temperature data quality is best in winter, with a CC value as high as 0.99, but there is an overestimation in the Western Pacific; summer temperature data quality is slightly poorer, with greater dispersion. For pressure data, the CC value is lowest in summer, averaging only 0.68, and in the spring, autumn, and winter in the Indian Ocean, the CC values are also relatively low, with significantly larger RMSE and MAE values. Additionally, the temperature data exhibit clear diurnal variation characteristics, while the pressure data show more pronounced regional characteristics. Although the overall trends of the ERA5 temperature and pressure data align with the VOS observations over global oceans, there are significant errors in specific numerical values, and these errors exhibit different characteristics across different seasons, oceanic regions, and diurnal variations. Therefore, when using ERA5 data for marine meteorology and ocean circulation studies, it is necessary to fully consider its applicability and limitations and conduct necessary validation and correction to ensure the accuracy and reliability of the research results.