Datasets

Accumulated Cyclone Energy (Verification) - Seasonal Forecast - SEAS5

This chart provides information on the verification of forecasts of Accumulated Cyclone Energy ...

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Accumulated Cyclone Energy - Seasonal Forecast - SEAS5

The ECMWF seasonal forecasts (SEAS5) are produced every month with a 51-member ensemble at a ...

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Indices (MUCAPE/Kindex/Totalx)

These charts show indices which indicate the susceptibility of the troposphere to support free convection. Typical values of the different indices depend on location and...

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Madden-Julian Oscillation (MJO) index - Sub-seasonal range forecast

This diagram shows time evolution of a Madden-Julian Oscillation (MJO) index. ...

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Mean wave period and mean wave direction

Mean wave period is the spectrally averaged period of the waves. Wave periods are shown in seconds using colour shading â€“ click on the middle icon to the bottom right for the scale...

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Sea ice concentration from 1978 to present derived from satellite observations

This dataset provides daily gridded data of sea ice concentration for both hemispheres derived from satellite passive microwave brightness temperatures. Sea ice is an important component of our climate system and a sensitive indicator of climate change. Its presence or its retreat has a strong impact on air-sea interactions, the Earth’s energy budget as well as marine ecosystems. It is recognised by the Global Climate Observing System as an Essential Climate Variable.

calendar_today Interval/period: Sun, 10/01/1978 - Mon, 09/29/2025

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Sea ice drift daily gridded data derived from satellite observations

This dataset provides daily gridded fields of sea ice drift vectors for both hemispheres derived from satellite passive microwave brightness temperatures and atmospheric reanalysis data. Sea ice is an important component of our climate system and a sensitive indicator of climate change. Its presence or retreat significantly affects ocean-atmosphere interactions, the Earth’s energy budget as well as marine ecosystems. It is classified as an Essential Climate Variable by the Global Climate Observing System.

calendar_today Interval/period: Tue, 01/01/1991 - Thu, 12/31/2020

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Sea ice edge and type daily gridded data from 1978 to present derived from satellite observations

This dataset provides daily gridded data of sea ice edge and sea ice type derived from brightness temperatures measured by satellite passive microwave radiometers. Sea ice is an important component of our climate system and a sensitive indicator of climate change. Its presence or its retreat has a strong impact on air-sea interactions, the Earth’s energy budget as well as marine ecosystems. It is recognized by the Global Climate Observing System as an Essential Climate Variable. Sea ice edge and type are some of the parameters used to characterise sea ice.

calendar_today Interval/period: Wed, 10/25/1978 - Wed, 09/24/2025

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Sea ice surface temperature derived from satellite observations

This dataset provides daily and monthly sea ice surface temperature (IST) fields over the polar oceans from 1982 to the present. The data are derived from thermal infrared measurements from a single satellite sensor type: the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (MetOp) satellites.

calendar_today Interval/period: Mon, 01/01/1979 - Tue, 09/30/2025

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Sea ice thickness gridded data for the Arctic derived from satellite observations

This dataset provides gridded sea ice thickness data for the Arctic, derived from satellite observations. Sea ice plays a vital role in the climate system, influencing air-sea interactions, the Earth’s energy balance, and marine ecosystems. It is recognised by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Sea ice thickness is a key characteristic used alongside other parameters such as concentration, edge, and type, all available in the Climate Data Store (CDS).

calendar_today Interval/period: Tue, 10/01/2002 - Sat, 04/12/2025

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Sea level gridded data from satellite observations for the global ocean from 1993 to present

This dataset provides gridded daily and monthly mean global estimates of sea level anomaly based on satellite altimetry measurements. The rise in global mean sea level in recent decades has been one of the most important and well-known consequences of climate warming, putting a large fraction of the world population and economic infrastructure at greater risk of flooding. However, changes in the global average sea level mask regional variations that can be one order of magnitude larger.

calendar_today Interval/period: Fri, 01/01/1993 - Sun, 12/31/2023

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Sea surface temperature daily gridded data from 1981 to 2016 derived from a multi-product satellite-based ensemble

This dataset provides global daily sea surface temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST) multi-product ensemble (GMPE) produced by the European Space Agency SST Climate Change Initiative (ESA SST CCI). The GMPE system was designed to allow users to compare the outputs from different SST analysis systems and understand their similarities and differences. Although originally intended for comparison of near real time data, it has also been used to compare long historical datasets.

calendar_today Interval/period: Tue, 09/01/1981 - Sat, 12/31/2016

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Essential climate variables for assessment of climate variability from 1979 to present

The Essential Climate Variables for assessment of climate variability from 1979 to present dataset contains a selection of climatologies, monthly anomalies and monthly mean fields of Essential Climate Variables (ECVs) suitable for monitoring and assessment of climate variability and change. Selection criteria are based on accuracy and temporal consistency on monthly to decadal time scales.

calendar_today Interval/period: Mon, 01/01/1979 - Wed, 04/01/2026

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Probabilities: lightning flash density

This chart shows probability information regarding lightning flash density derived from the ...

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Probabilities: mean wave period

This chart shows probability information regarding mean wave period derived from the ECMWF ...

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Probabilities: significant wave height

This chart shows probability information regarding significant wave height derived from the ...

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Probabilities: mean wave period (day 10-15)

These charts show the probability of various mean periods of ocean waves 10-15 days ahead. The ...

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Tropical Storm Standardised Density - Seasonal Forecast - SEAS5

The ECMWF seasonal forecasts (SEAS5) are produced every month with a 51-member ensemble at a ...

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Windsea: mean period of waves and direction

Mean windsea wave direction is the spectrally averaged direction of propagation of the windsea waves (weighted by wave height). Arrow length is proportional to the speed of wave propagation...

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Windsea: significant wave height and mean direction

Significant windsea wave height can be shown to correspond to the average wave height of the top one-third highest windsea waves. Wave heights are shown in metres using colour shading...

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S2S global sub-seasonal to seasonal ensemble real-time forecasts from multiple NWP and research centres since 2015

The Sub-seasonal To Seasonal dataset (S2S) consists of global ensemble real-time forecasts and reforecasts from thirteen numerical weather prediction (NWP) and research centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.

calendar_today Interval/period: Thu, 01/01/2015 - Wed, 05/06/2026

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S2S global sub-seasonal to seasonal ensemble reforecasts from multiple NWP and research centres since 2015

The Sub-seasonal To Seasonal dataset (S2S) consists of global ensemble real-time forecasts and reforecasts from thirteen numerical weather prediction (NWP) and research centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.

calendar_today Interval/period: Tue, 03/01/2011 - Tue, 06/09/2026

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