Sea Level Trends and Extremes

Tide gauges are used to measure sea level change. National Ocean Service gauges use microwave, pressure, and acoustic water level sensors, typically placed on a pier or other coastal structure. Tide gauges measure the height of the water along the coast relative to a specific point on land. If the land is moving, changes in sea levels over time will include this motion. These measurements are used to distinguish short-term fluctuations, like tides and storms, from long-term trends by analyzing data over extended periods of time.

• Relative sea level is the height of the ocean relative to a specific point on land. It accounts for both changes in the ocean's surface and vertical land movements. Relative sea level changes can vary significantly from place to place due to land uplift and subsidence
• Regional sea levels can differ from global trends and are spatial variations in sea level changes due to factors like ocean currents and local climate patterns.
• Global sea level refers to the average height of the entire ocean surface worldwide.

No, sea levels are not uniformly rising across the Nation. These differences can be attributed to a number of factors like changing ocean circulation patterns, changes in the Earth’s gravity fields, and vertical land motion (i.e. subsidence or rebound).

• Trends refer to observed patterns in sea level data over time. Scientists use methods like linear trends (straight-line averages) and higher order models (e.g. quadratic fits) to analyze these patterns. Linear trends are useful for identifying steady increases or decreases in sea level over time, while quadratic fits capture changes in the rate of sea level rise, reflecting periods of acceleration or deceleration. Understanding these trends helps anticipate future sea level changes and their potential impacts on coastal areas.
• Projections explore different modeled scenarios, providing trajectories of possible future sea level changes. NOAA’s Sea Level Trends and Extremes product does not display projections. For forward-looking data, refer to NOAA’s Sea Level Calculator.

• Over short time periods, interannual to annual variability in sea levels is driven by natural ocean processes, like El Niño and La Niña events.
• Over longer time periods, like decades to centuries, sea level change is primarily driven by ice sheet loss, glacial isostatic adjustment, and thermal expansion.
• Vertical land motion can affect local sea levels on both short and long timescales.

• Vertical land motion plays a large role in historic, present, and future sea level change.
• Over decadal timescales, land sinking or uplifting can cause noticeable changes in relative sea levels.
• Earthquakes or man-made forces like fluid extraction can cause rapid land uplift or subsidence.
• Two stations that are relatively close to each other may have drastically different relative trends due to local conditions.

No, some trends are more accurate than others. Sea level trends that are based on shorter records (30 years or less) are not as precise. Areas where sea levels are strongly influenced by interannual variations, like El Niño or La Niña events, may have more uncertainty in their trend estimates.

Extreme water levels occur when water levels rise much higher or drop much lower than average due to tides, storms, and other weather conditions. These events can cause flooding, erosion, and damage to coastal areas. As sea levels rise, what is considered extreme today will become more common and no longer considered extreme in the future.

Annual Exceedance Probability (AEP) and Average Return Intervals (ARI) both refer to statistical representations of the likelihood of water levels either rising to or falling to a certain height level within a given timespan.

• AEP’s indicate the probability of a certain water level being met or exceeded in any single year, typically expressed as a percentage. For example, 1% AEP represents a 1-in-100 (or 1%) chance of that flood level being equaled or exceeded in any given year. This methodology is typically the default statistic used by NOAA CO-OPS.
• ARI’s, also known as the “return period,” estimates the average length of time (in years) between events of the same or greater magnitude. The example of a 1% AEP above is equivalent to an ARI of 1 event every 100 years that exceeds a certain height. This methodology is used in the Regional Frequency Analysis.

Methodologically, one of the key differences between these methods is the time frame in which measurements are taken. AEP relies exclusively on a single maximum or minimum value per year. In contrast, ARI is more flexible and can include multiple events within the same year, as long as they exceed a specific threshold.

These statistics enable communities to evaluate the significance of a particular flooding event against the historical record. They are also used to model the most extreme water level elevations within a time window (e.g. what is the highest anticipated water level relative to mean higher high water within a 20 year period at a specific location). Planners can use this information to evaluate flood risks for building resilient infrastructure and for emergency response planning.

• Sea Level Trends: NOAA’s sea level trend rates are computed with the intent of having uncertainty below 1.5 millimeters per year. Uncertainty in sea level trends depends on the period of record, which can vary from a few decades to over a century, and the environment in which the data are collected. For example, a station in a calm and predictable environment with 35 years of data may have a lower uncertainty than a station with 50 years of data in an environment with strong interannual variability.
• Extreme Water Levels: Uncertainty in extreme water level statistics depends on the number of the data points within a record, the frequency of interest, and the environment in which the data are collected. For example, if you consider an extreme value model for Charleston, South Carolina, the most frequent extreme events, those with a 99% chance of occurrence (e.g., high tide flooding), will have many data points within the history of observation at or around that level. In contrast, the rarest events, those with a <1% chance of occurrence (e.g. Hurricane Hugo), will have significantly fewer data points in the history of observation and will have higher uncertainty.

Sea Level Trends and Extremes displays data on different spatial scales to provide meaningful context and comparison of sea level means and extremes.

• Station View is useful for focusing on a single tide gauge and its relative sea level and extremes data record.
• Regional View is useful for comparing a station’s data against other locations within a region. This information can be used to evaluate how a point of interest aligns or differs from neighboring tide gauge.