Rising sea levels pose a potential threat to the densely populated areas along the Indian coastline and the low-lying islands, and cause disastrous impacts to coastal and offshore structures. Large fluctuations in sea surface temperature (SST) in the North Indian Ocean (NIO) is one of the contributing factors in inducing significant changes in sea level along the Indian coastline. Therefore, it is important to quantify the trends in sea level rise (SLR) in association with SST in this region. In this study, the seasonal climatology and variability of sea level anomaly (SLA) and SST is examined in the NIO (65 °E–92.5°E, 4.5 °N–25 °N). A comparative study is conducted based on two different datasets by using the reconstructed sea surface height anomalies (SSHA) for 58 years from 1952–2009 and Archiving, Validation and Interpretation of Satellite Oceanographic (AVISO) SLA dataset for 27 years from 1993–2019.The spatial correlation maps between SLA and SST reveal that AS exhibits strong positive correlation as compared to BoB throughout the year. In addition, the rate of increase in sea level is examined at twelve locations along the Indian coastline for pre-satellite era (1952–2009) and satellite altimeter era (1993–2019). In recent decades, a higher rate of increase as compared to long term trends (1952–2009) is observed, i.e., even exceeding the global mean SLR trend (3.2 mm yr ⁻¹). The highest rate of increase in annual sea level is observed at Mangalore ($r=0.4$ cm) and the lowest is observed at Haldia ($r=0.03$ cm) during the recent decades. However, during 1952-2009, the maximum rate of annual SLR is found at Okha ($r=0.21$ cm) and the minimum at Vishakhapatnam ($r=0.11$ cm). The analysis clearly elucidates that the sea level is continuously rising and accelerating and, four Indian coastal cities, namely, Vishakhapatnam, Mangalore, Mumbai and Chennai are the most susceptible of all.

海平面上升对印度海岸线沿线人口稠密地区和低洼岛屿构成潜在威胁，并对沿海和近海结构造成灾难性影响。北印度洋 (NIO) 海面温度 (SST) 的大幅波动是导致印度海岸线海平面发生显着变化的因素之一。因此，量化与该地区 SST 相关的海平面上升 (SLR) 趋势非常重要。在这项研究中，研究了 NIO（65 °E–92.5 °E，4.5 °N–25 °N）中海平面异常 (SLA) 和 SST 的季节性气候学和变异性。通过使用 1952-2009 年 58 年的重建海面高度异常 (SSHA) 和存档，基于两个不同的数据集进行了比较研究，从 1993 年到 2019 年的 27 年卫星海洋学 (AVIO) SLA 数据集的验证和解释。 SLA 和 SST 之间的空间相关图显示，与 BoB 相比，AS 全年表现出强烈的正相关性。此外，在卫星前时代（1952-2009 年）和卫星高度计时代（1993-2019 年）沿印度海岸线的 12 个地点检查了海平面上升率。近几十年来，观察到与长期趋势（1952-2009）相比更高的增长率，即甚至超过全球平均 SLR 趋势（每年 3.2 毫米）在卫星前时代（1952-2009 年）和卫星高度计时代（1993-2019 年）沿印度海岸线的 12 个地点检查了海平面上升率。近几十年来，观察到与长期趋势（1952-2009）相比更高的增长率，即甚至超过全球平均 SLR 趋势（每年 3.2 毫米）在卫星前时代（1952-2009 年）和卫星高度计时代（1993-2019 年）沿印度海岸线的 12 个地点检查了海平面上升率。近几十年来，观察到与长期趋势（1952-2009）相比更高的增长率，即甚至超过全球平均 SLR 趋势（每年 3.2 毫米）^-1 )。在芒格洛尔（Mangalore）观察到年度海平面的最高增长率（$r=0.4$ cm)，最低的是在 Haldia ($r=0.03$ 厘米）在最近几十年。然而，在 1952-2009 年期间，在 Okha ($r=0.21$ cm) 和 Vishakhapatnam ($r=0.11$ 厘米）。分析清楚地表明，海平面在不断上升和加速，其中四个印度沿海城市，即维沙卡帕特南、门格洛尔、孟买和金奈最容易受到影响。