Global sea levels have been steadily rising over the past three decades, with an average increase of *** millimeters per year. In January 2024, the mean sea level was *** millimeters higher compared to the same month in 1993. Contributing factors to sea level rise The upward trend of the global sea level is primarily attributed to the effects of climate change, particularly the rise in global ocean temperatures and the subsequent expansion of water, as well as the increased volume resulting from the melting of ice caps and glaciers. Sea ice extent across the globe has been consistently reporting historic lows, with 2023 being the worst year since records started. The rise will continue, despite the scenario Regardless of the greenhouse gas emissions scenario chosen, the global sea level is projected to continue increasing at least through the end of the century. Even under a very low emissions scenario, it is estimated that the overall rise in sea level worldwide will be approximately ** millimeters between 2040 and 2060, or *** millimeters per year. For a high emissions scenario, the rise could be as high as *** millimeters per year, twice the rate of the past three decades.

'''DEFINITION'''

The sea level ocean monitoring indicator has been presented in the Copernicus Ocean State Report #8. The sea level ocean monitoring indicator is derived from the DUACS delayed-time (DT-2024 version, “my” (multi-year) dataset used when available, “myint” (multi-year interim) used after) sea level anomaly maps from satellite altimetry based on a stable number of altimeters (two) in the satellite constellation. The product is distributed by the Copernicus Climate Change Service and the Copernicus Marine Service (SEALEVEL_GLO_PHY_CLIMATE_L4_MY_008_057). At each grid point, the trends/accelerations are estimated on the time series corrected from regional GIA correction (GIA map of a 27 ensemble model following Spada et Melini, 2019) and adjusted from annual and semi-annual signals. Regional uncertainties on the trends estimates can be found in Prandi et al., 2021.

'''CONTEXT'''

Change in mean sea level is an essential indicator of our evolving climate, as it reflects both the thermal expansion of the ocean in response to its warming and the increase in ocean mass due to the melting of ice sheets and glaciers(WCRP Global Sea Level Budget Group, 2018). According to the IPCC 6th assessment report (IPCC WGI, 2021), global mean sea level (GMSL) increased by 0.20 [0.15 to 0.25] m over the period 1901 to 2018 with a rate of rise that has accelerated since the 1960s to 3.7 [3.2 to 4.2] mm/yr for the period 2006–2018. Human activity was very likely the main driver of observed GMSL rise since 1970 (IPCC WGII, 2021). The weight of the different contributions evolves with time and in the recent decades the mass change has increased, contributing to the on-going acceleration of the GMSL trend (IPCC, 2022a; Legeais et al., 2020; Horwath et al., 2022). At regional scale, sea level does not change homogenously, and regional sea level change is also influenced by various other processes, with different spatial and temporal scales, such as local ocean dynamic, atmospheric forcing, Earth gravity and vertical land motion changes (IPCC WGI, 2021). The adverse effects of floods, storms and tropical cyclones, and the resulting losses and damage, have increased as a result of rising sea levels, increasing people and infrastructure vulnerability and food security risks, particularly in low-lying areas and island states (IPCC, 2019, 2022b). Adaptation and mitigation measures such as the restoration of mangroves and coastal wetlands, reduce the risks from sea level rise (IPCC, 2022c).

'''KEY FINDINGS'''

The altimeter sea level trends over the [1999/02/21 to 2023/12/31] period exhibit large-scale variations with trends up to +10 mm/yr in regions such as the western tropical Pacific Ocean. In this area, trends are mainly of thermosteric origin (Legeais et al., 2018; Meyssignac et al., 2017) in response to increased easterly winds during the last two decades associated with the decreasing Interdecadal Pacific Oscillation (IPO)/Pacific Decadal Oscillation (e.g., McGregor et al., 2012; Merrifield et al., 2012; Palanisamy et al., 2015; Rietbroek et al., 2016).

Prandi et al. (2021) have estimated a regional altimeter sea level error budget from which they determine a regional error variance-covariance matrix and they provide uncertainties of the regional sea level trends. Over 1993-2019, the averaged local sea level trend uncertainty is around 0.83 mm/yr with local values ranging from 0.78 to 1.22 mm/yr.

'''DOI (product):''' https://doi.org/10.48670/moi-00238

In 2024, the global ocean surface temperature was 0.97 degrees Celsius warmer than the 20th-century average. Oceans are responsible for absorbing over 90 percent of the Earth's excess heat from global warming. Departures from average conditions are called anomalies, and temperature anomalies result from recurring weather patterns or longer-term climate change. While the extent of these temperature anomalies fluctuates annually, an upward trend has been observed over the past several decades. Effects of climate change Since the 1980s, every region of the world has consistently recorded increases in average temperatures. These trends coincide with significant growth in the global carbon dioxide emissions, greenhouse gas, and a driver of climate change. As temperatures rise, notable decreases in the extent of arctic sea ice have been recorded. Outlook An increase in emissions from the use of fossil fuels is projected for the coming decades. Nevertheless, global investments in clean energy have increased dramatically since the early 2000s.

Sea levels are projected to rise in India under various Shared Socioeconomic Pathways (SSP). Under the SSP1-2.6 low emission scenario, it is expected that sea levels in India will rise 8.16 centimeters (cm) during the next decades, and 16.78 cm by mid-century, relative to the historic baseline. Sea levels will continue rising to reach 34.62 cm by 2099, following the same scenario.

This metadata record is for AfA product AfA 010. Surge Shape data is part of Coastal Design/Extreme Sea Levels,a GIS dataset and supporting information providing design / extreme sea level and typical surge information around the coastline of the UK, including England, Wales, Scotland, Northern Ireland, Isle of Man and Jersey. The information is relevant under present day (year 2018) conditions and does not account for future changes due to climate change, such as sea level rise. This is a specialist dataset which informs on work commenced around the coast ranging from coastal flood modelling, scheme design, strategic planning and flood risk assessments.

Surge Shape data is an Excel spreadsheet containing numeric data and graphs, linked to the Surge Shape locations data via common fields.

This 2018 update to the Coastal Design Sea Levels dataset was carried out in partnership for the UK Coastal Flood Forecasting partnership, which includes the Environment Agency (EA), Scottish Environment Protection Agency (SEPA), Natural Resources Wales (NRW) and the Department for Infrastructure Northern Ireland (DfINI).

A bundle download of all Coastal Design Sea Levels datasets is available from this record. Please see individual records for full details and metadata on each product.

This map shows coastal flooding around Honolulu, Hawaii due to 6 feet (1.829 m) of sea level rise. This scenario was derived using a National Geospatial Agency (NGA)-provided digital elevation model (DEM) based on LiDAR data of the Honolulu area collected in 2009. This "bare earth" DEM (vegetation and structures removed) was used to represent the current topography of the study area above zero elevation for the urban corridor stretching from Honolulu International Airport to Waikiki and Diamond Head along the south shore of Oahu. The accuracy of the DEM was validated using a selection of 16 Tidal Benchmarks located within the study area. The single value tidal water surface of mean higher high water (MHHW) modeled at the Honolulu tide gauge was used to represent sea level for the purposes of this study. Water levels are shown as they would appear during the highest high tides (excluding wind-driven tides). Data produced in 2014 by Dr. Charles "Chip" Fletcher of the department of Geology & Geophysics (G&G) in the School of Ocean and Earth Science and Technology (SOEST) of the University of Hawaii at Manoa. Supported in part by the NOAA Coastal Storms Program (CSP) and the University of Hawaii Sea Grant College Program. These data do not consider future changes in coastal geomorphology and natural processes such as erosion, subsidence, or future construction. These data do not specify timing of inundation depths and are not appropriate for conducting detailed spatial analysis. The entire risk associated with the results and performance of these data is assumed by the user. These data should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.

The R code that was used to graph the acid dissociation data for H3As(III)O3 in S4 File.

Dataset contains a combined monthly sea level records as observed from the year 1994 - 2018. It is well acknowledged that sea level rise is already affecting Solomon Island communities. The Solomon Islands Second National Communication cites satellite altimetry readings indicating that the country is experiencing sea-level rise at a rate of 8-10 mm per year. The monthly sea level data contains a relative sea level trend of –5.7 mm/year.

This dataset explores the variability in glacial-interglacial surface hydrography in the western Indian Ocean across the middle to late Pleistocene. Here, we provide 1kyr resolution Mg/Ca-based sea surface temperatures and surface oxygen isotope ratios of seawater (ice volume corrected) as proxy for surface palaeo-salinity from surface dwelling foraminifera Globigerinoides ruber from International Ocean Discovery Program core site U1476 located in the Mozambique Channel, which we use in combination with other records to create Indian Ocean sea surface salinity and sea surface temperature stacks. The data show increases in sea surface temperature and salinity during glaciation, with maximum temperature and salinity occurring at glacial maxima, prior to global deglaciations as indicated by benthic oxygen isotopes, a proxy for global ice volume. Lead-lag analyses were conducted using cross-spectral analysis between sea surface temperatures, salinity, and benthic oxygen isotopes. In parallel, sea-to-land pixel ratios from the ANICE-SELEN model across the Indonesian Archipelago show changes in land surfacing in the Indonesian archipelago due to globally sinking sea levels. The increase in surface temperature and salinification at U1476 occurs at the same time as major land surfacing in the Indonesian Archipelago suggesting a mechanistical link between land surfacing due to global sea level lowering, and changes in Indian Ocean surface hydrography that appears to be a resulting reduction in the considerably fresher Indonesian throughflow entering the Indian Ocean.

The surface temperature of the world's oceans reached new record levels in the first months of 2024, continuing the trend started in April 2023. As of August 6, 2024, the global sea surface temperature reached 20.98 degrees Celsius, an increase of 0.76 degrees compared to the 1982-2010 average. Overall, 2024 was a year of record temperatures on land and in the sea, with a temperature anomaly of 1.29 degrees with respect to the 20th century average. As of May 2025, temperatures this year remain lower than 2024 temperatures.

The world's oceans are becoming increasingly acidic, with the average ocean pH falling from 8.11 in 1985 to 8.05 in 2022. This seemingly small change represents a significant increase in acidity, damaging the fine chemical balance of the oceans and posing a risk to marine ecosystems. The more emissions, the more acidic As global CO2 emissions continue to rise, the oceans absorb more CO2 per year, playing a crucial role in regulating atmospheric CO2 levels. The increased dissolution of CO2 in seawater causes the oceans’ pH to decrease. The acidification of the oceans creates conditions that dissolve minerals such as carbonates, which are the backbone of reefs and marine life’s shells and skeletons. In addition, certain species of harmful algae proliferate in acidified waters, putting fish, marine mammals, and the full food chain in danger. Warmer oceans on top of acidification Acidification is not the only climate change-related issue the oceans must adapt to. In 2023, the average ocean surface temperature worldwide was almost one degree Celsius higher than the 20th century average. Such departures from average conditions are called anomalies, and although they fluctuate, the global ocean surface temperature anomaly has shown a marked upward trend over the past decades. A warming ocean brings a series of cascading effects, including the melting of sea ice, sea level rise, and marine heatwaves. On top of that, less carbon sinks to the deep ocean in warmer waters, making them a less efficient carbon pool and therefore aggravating climate change.

Sea levels are projected to rise in the Netherlands under various Shared Socioeconomic Pathways (SSP). Under the SSP1-2.6 low emission scenario, it is expected that sea levels in the Netherlands will rise 11.78 centimeters (cm) during the next decades, and 22.44 cm by the mid-century, relative to the historic baseline. Sea levels will continue rising to reach 41.84 cm by 2099, following the same scenario.

The project investigates (a) how staged global political media events (i.e. the global climate summits) are produced, and (b) which discursive effects these events have on national climate debates in the media of five leading democratic countries around the world, namely the U.S., Germany, India, South Africa and Brazil.

I. Formal and general content related categories 1. Formal variables: article-ID; coder-ID; title (main headline of the article); date of publication; media outlet (newspaper, magazine or news website in which the article was published); length of the article; format of the article (fact-based article, opinion-based article, interview, press review, stand-alone visual image as an independent article, letter to the editor, other); placement of the article (front page article or cover story, article inside the newspaper and magazine referenced on the front page, article inside the newspaper and magazine without reference on the front page); section of newspaper, magazine and news website; author of the article.

1. Content variables: article trigger (institutional events, unpremeditated (unplanned) events, communicative events, other event); UN Climate Change Conferences (COPs) reference; country references; international / transnational institutional references.

II. Visual level 1. Formal variables: visual present; photo present; number of visual images; number of photos; visual image-ID, type of visual image (photograph, photomontage, chart, map or table, cartoon / caricature, official logo of COP, topical vignette by newspaper or magazine); source of visual image. 2. Visual framing (if the visual image is a photograph or photomontage): denotative level: institutional reference depicted in the photo; content of the photo: urban landscape, natural landscape (woods, mountains and/ or lake, plants and/ or grassland / meadow), ocean and/or ocean coast, snow, ice, glacier, desert or steppe, polar bear, other animals, transportation or conventional traffic, agriculture, conventional energy generation, green technology, other industry / technology, PR stunt installation; person(s) depicted in the photo: political actor, NGO representative(s), business representatives, scientists, celebrities, police / security personnel, ordinary citizen(s), other type of person; origin of depicted person; activity of depicted person (e.g. symbolic activity, demonstration and other form of protest, etc.); location of depicted scene.

Stylistic level: camera angle, distance / field size of photo.

III. Narration: 1. Narrative characteristics: narratively (dramatization, emotion, narrative personalization, fictionalization, stylistic ornamentation); narrative genre: overall theme (everyday business, failure after struggle, triumph over adversity, struggle over destiny or planet or civilization, political or social conflict); tone (fatalistic, optimistic, unexcited, neutral, passionate, pessimistic); expected outcome; no conceivable outcome. 2. Character specification: character as victim: narrative role: victim present; victim type; victim name; victim action taken; character as villain: narrative role: villain present; villain type; villain name; villain action taken; character as hero: narrative role: hero present; hero type; hero name; hero action taken; sum of all actors in the article; sum of NGO representatives, politicians, representatives, international organizations, business representatives, scientists, journalists, citizens, and other actors.

IV. Actor-statement level Actors: actor-statement-ID; name of the actor; type of actor; occupation / office of actor; origin of actor; type of quotation; prominence of actor-statement; type of ´we´ reference; frames: denial of reality of global warming; denial of problematic character / urgency of action; cntral aspect of problem definition: increase of temperature, extreme weather, melting ice or glaciers / rising sea levels, economic opportunities due to global warming, economic difficulties and hardships due to global warming, other societal consequences; causal attribution (situations or processes the actor identifies as causing or contributing to global warming): natural causes; anthropogenic causes (burning of fossil fuels / greenhouse gas emissions, deforestation, colliding national interests, other causes; countries responsible for causing global warming; endorsed and rejected remedies (no action should be taken, clean energy, reforestation and avoided deforestation); adaption action: adaption in agricultural production; adjusting political process: adoption of new legally binding, all-inclusive treaty on emission cuts; stronger focus on local efforts / working on the ground; other measures: financial assistance to disadvantaged countries; attributed responsibility for solving the problem.

Additionally coded was: country; COP (COP 16 Cancun, COP 17 Durban, COP 18 Doha, COP 19 Warsaw); 4 Cluster Solution Frames (political dispute, common...

Trends of Atmospheric Carbon Dioxide measurements from the Mauna Loa Baseline Observatory, Hawaii, United States.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 hourly data on single levels from 1940 to present".

This Feature Layer is included in the Mitigating Marshes Against Sea Level Rise: Thin Layer Placement Experiment application.The National Estuarine Research Reserve (NERR) System Science Collaborative funded a two-year experiment at 8 different NERR sites to provide broad geographic scale, including Chesapeake Bay NERR in Virginia. The three core research questions they aim to answer include: “Is sediment addition an effective adaptation strategy for marshes in the face of sea level rise? How does marsh resilience respond to different levels of sediment addition? How do low versus high marsh habitats differ in their response to this restoration strategy?”.This Story Map is a tool for 6th-12th grade teachers to help teach students about marshes and thin layer placement restoration techniques by exploring maps, videos, and images. Students will analyze how vegetation has changed in the Chesapeake Bay National Estuarine Research Reserve in Virginia (CBNERR-VA) marsh experiment plots in the first year of monitoring. They will evaluate images and graphs different treatments and determine which could be used as a possible restoration technique to combat sea level rise in marshes.Data: https://www.vims.edu/cbnerr/resources/gis-data-layers/index.php

This Web Map is included in the Mitigating Marshes Against Sea Level Rise: Thin Layer Placement Experiment application.The National Estuarine Research Reserve (NERR) System Science Collaborative funded a two-year experiment at 8 different NERR sites to provide broad geographic scale, including Chesapeake Bay NERR in Virginia. The three core research questions they aim to answer include: “Is sediment addition an effective adaptation strategy for marshes in the face of sea level rise? How does marsh resilience respond to different levels of sediment addition? How do low versus high marsh habitats differ in their response to this restoration strategy?”.This Story Map is a tool for 6th-12th grade teachers to help teach students about marshes and thin layer placement restoration techniques by exploring maps, videos, and images. Students will analyze how vegetation has changed in the Chesapeake Bay National Estuarine Research Reserve in Virginia (CBNERR-VA) marsh experiment plots in the first year of monitoring. They will evaluate images and graphs different treatments and determine which could be used as a possible restoration technique to combat sea level rise in marshes.Data: https://www.vims.edu/cbnerr/resources/gis-data-layers/index.php

Trends of Atmospheric Methane measurements from marine surface sites.

Since the 1980s, the annual temperature departure from the average has been consistently positive. In 2024, the global land and ocean surface temperature anomaly stood at 1.29 degrees Celsius above the 20th-century average, the largest recorded across the displayed period. What are temperature anomalies? Temperature anomalies represent the difference from an average or baseline temperature. Positive anomalies show that the observed temperature was warmer than the baseline, whereas a negative anomaly indicates that the observed temperature was lower than the baseline. Land surface temperature anomalies are generally higher than ocean anomalies, although the exact reasons behind this phenomenon are still under debate. Temperature anomalies are generally more important in the study of climate change than absolute temperature, as they are less affected by factors such as station location and elevation. A warming planet The warmest years have been recorded over the past decade, with the highest anomaly in 2024. Global warming has been greatly driven by increased emissions of carbon dioxide and other greenhouse gases into the atmosphere. Climate change is also evident in the declining extent of sea ice in the Northern Hemisphere. Weather dynamics can affect regional temperatures, and therefore, the level of warming can vary around the world. For instance, warming trends and ice loss are most obvious in the Arctic region compared to Antarctica.