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There is not 100% confidence in the elevation data and/or mapping process. It is important not to focus on the exact extent of inundation, but rather to examine the level of confidence that the extent of inundation is accurate (see mapping confidence tab).

The four relative sea level rise (RSL) scenarios shown in this tab are derived from the 2022 Sea Level Rise Technical Report using the same methods as the U.S. Army Corps of Engineers Sea Level Change Curve Calculator. These new scenarios were developed by the U.S. Sea Level Rise and Coastal Flood Hazard Scenarios and Tools Interagency Task Force as input into the U.S. Global Change Research Program Sustained Assessment process and, Fifth National Climate Assessment. These RSL scenarios provide an update to the NOAA 2017 scenarios, which were developed as input to the Fourth National Climate Assessment.

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Note: We do not show the low scenario, as it is a continuation of the current global trend since the early 1990s and has been determined to have a low probability of occurring by 2100. Furthermore, this scenario would be associated with low levels of risk even if it did occur.

Another important change from the 2017 scenarios is the exclusion of the extreme (2.5 meter) scenario. Based on the most recent scientific understanding, and as discussed in the IPCC AR6, the uncertain physical processes that could lead to much higher increases in sea level are now viewed as less plausible in the coming decades before potentially becoming a factor toward the end of the 21st century. A GMSL increase of 2.5 meters is thus viewed as less plausible and the associated scenario has been removed.

Blue areas denote a high confidence of inundation, orange areas denote a high degree of uncertainty, and unshaded areas denote a high confidence that these areas will be dry given the chosen water level.

In this application 80% is considered a high degree of confidence such that, for example, the blue areas denote locations that may be correctly mapped as 'inundated' more than 8 out of 10 times. Areas with a high degree of uncertainty represent locations that may be mapped correctly (either as inundated or dry) less than 8 out of 10 times. For a detailed description of the confidence levels and their computation, see the methods document.

Predictions represent the potential distribution of each wetland type (see legend) based on their elevation and how frequently they may be inundated under each scenario. As sea levels increase, some marshes may migrate into neighboring low-lying areas, while other sections of marsh will change type or be lost to open water.

Note: We do not show the low scenario as it is a continuation of the current global trend since the early 1990s and has been determined to have a low probability of occurring by 2100. Furthermore, this scenario would be associated with low levels of risk even if it did occur.

The Social Vulnerability Index, which shows areas of high human vulnerability to hazards, is based on population attributes from Census 2010 (e.g., age and poverty) and the built environment. By looking at the intersection of potential sea level rise and vulnerable Census tracts, one can get an idea of how vulnerable populations might be affected by sea level rise. Dark red indicates tracts having a high vulnerability, and the lighter reds indicate decreasing vulnerability.

The purpose of this map viewer is to provide federal, state, and local coastal resource managers and planners with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses best-available, nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help estimate impacts and prioritize actions for different scenarios.

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Differential Pressure (DP) Level Measurement uses pressure readings and specific gravity to output level. DP Level is a common measurement technique that is used in a wide variety of applications and industries. Solutions include standard transmitter connections and integrated transmitters with direct or remote mount seals that can be configured in tuned, balanced, and electronic systems. Additional Wireless options are also available.

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For typical street, waterway or railway crossings over bridges or tunnels, layer=* should be used instead. Roads or other ways passing through buildings should be marked with tunnel=building_passage; they should be only marked with level if there is a strong relation to the corresponding level of the building.

The value of the level=* is numerical and used to denote the vertical order of the floors. Usually, level=0 is the ground floor, level=1 the floor above it and basement floors start with level=-1. However, if a building sits at an uneven elevation, the numbers begin at the lowest exposed floor for consistency with the Simple 3D Buildings specification's building:levels=* key. For example, a shop located in a shopping mall's fully underground basement would be tagged level=-1, whereas an entrance to a house's walk-out basement would be tagged level=0.

A building may skip certain level numbers, such as floor 13 in Western countries or floors 4 and 14 in Chinese-speaking countries. Tag the surrounding building with, e.g., non_existent_levels=13 to prevent data consumers from miscounting features on floors above the skipped level.

In general, the level=* key ignores these distinctions in favor of the zero-based numbering scheme, because the level=* key was originally envisioned as a machine-readable key for 3D building rendering. Data consumers that support the Simple Indoor Tagging require values to be numeric and consecutive, even for basements and mezzanines that in reality are known by unpredictable mnemonics such as "B", "B1", "G", "M", and "2M".

level=* values are largely zero-based even in many regions where the one-based numbering system is prevalent in everyday life. However, mappers overwhelmingly skip 0 in Kazakhstan, Korea, and Mongolia, beyond any rate that could be explained by mappers treating 0 as an implicit default value:

Regardless of each country's local tagging convention, inexperienced mappers unaware of the convention may occasionally tag level=* based on the one-based system.[1] Some one-based tagging may have also been introduced because of a previous version of this article. Data consumers may be able to account for some discrepancies in floor numbering. For example, if some features inside a building have a level=* value greater than the building's building:levels=* value and none of the features in the building is tagged level=0, then a data consumer could decrement all the level=* values by one.

When a building uses non-numeric or otherwise non-standard floor designations, tag the individual features on a floor with level:ref=*, ideally in addition to level=* to prevent mishandling by data consumers. For example, the Siam Paragon mall in Bangkok consists of the following floors: B, G, M, 1, 2, 3, 4, 4A, and 5.[2]. A shop on level 4A can then be tagged with level:ref=4A.

Tagging shops exclusively with level:ref=* can be problematic because a data consumer cannot reliably determine the relative vertical order of each floor in the building. To consolidate this information, the Simple Indoor Tagging scheme suggests creating an outline for each level, tagged with indoor=level, adding both level=* and level:ref=* to it. This also works the other way round - if only level=* is defined on the individual shops.

Level range: level=-1;0 room=yes is a room which goes over (spans) two levels. It's the same room that is accessible on both levels. Often there are doors to each one. If a room is repeated on multiple levels, (it's a different room on another level but has identical dimensions and position in the building,) draw a separate element for each room or use repeat_on=*.

Use a minus sign to specify a range of positive numbers with no missing values.e.g. The elevator of a 32 storey highrise with two basement levels: level=-2;-1; 0-31 This shows connectivity to multiple levels for indoor navigation.

Long-term sea level rise will affect the extent, frequency, and duration of coastal flooding events. High-tide flooding events that occur only a few times a year now may occur once a month, or once a week in the coming decades. These same water level changes may also increase coastal erosion and groundwater levels. Elevated groundwater levels can lead to increased rainfall runoff and compromised underground infrastructure, such as public utilities, septic systems, and structural foundations. Higher water levels also mean deadly and destructive storm surges, wave impacts, and rainwater are unable to drain away from homes and businesses. ff782bc1db