Gridded satellite altimetry data of the Arabian Gulf during 1993–2017 were utilized to determine the relative contributions of sea surface temperature, sea level pressure, wind speed, and evaporation reanalysis data on the variability of remotely sensed sea level anomaly (SLA), which shows a mean increasing trend of 3 mm/yr. Sea surface temperature had the strongest effect on SLA, contributing 38.40% of the variability. Sea level pressure had the second greatest effect at 17%. Wind speed did not have a significant contribution to SLA variability, while evaporation had an effect of approximately 4.13%. EOF analysis was used to determine the mode of SLA variability. The first six modes explained more than 90% of the variability in SLA. The first mode, which represents the annual signal, explains 80.30% of the variability, while the second mode resolves approximately 6.80%. The contributions of different factors on the first and second modes show that the sea surface temperature and sea level pressure dominate the influence on the annual signal. Wind speed did not show a strong effect on either annual or semiannual fluctuations, while the main contribution on the semiannual signal was due to evaporation with 9.62%.

利用阿拉伯湾1993-2017年的栅格化卫星测高数据，确定了海面温度，海平面压力，风速和蒸发再分析数据对遥感海平面异常（SLA）变异性的相对贡献。平均每年增加3毫米。海面温度对SLA的影响最大，贡献了38.40％的变化。海平面压力的第二大影响是17％。风速对SLA的变化没有显着影响，而蒸发的影响约为4.13％。EOF分析用于确定SLA变异性的模式。前六个模式解释了SLA中90％以上的可变性。第一种模式代表年度信号，解释了80.30％的可变性，而第二种模式的解析度约为6.80％。不同因素对第一和第二模式的贡献表明，海面温度和海平面压力对年信号的影响占主导地位。风速对年度或半年度波动都没有显示出强烈的影响，而对半年度信号的主要贡献是由蒸发引起的，为9.62％。