The 850 hPa level is usually just above the boundary layer and at this level the day-night variation in temperature is generally negligible...

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open_in_newview in Open Charts

This chart shows 7-day mean anomalies of 500hPa geopotential height from the ECMWF Sub-seasonal ...

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open_in_newview in Open Charts

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

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open_in_newview in Open Charts

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

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open_in_newview in Open Charts

Various thermall comfort parameters showing thermal comfort

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open_in_newview in Open Charts

This chart shows 7-day mean anomalies of temperature at 10hPa from the ECMWF Sub-seasonal range ...

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open_in_newview in Open Charts

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

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open_in_newview in Open Charts

Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.

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open_in_newview in Open Charts

Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.

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open_in_newview in Open Charts

Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.

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open_in_newview in Open Charts

Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.

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open_in_newview in Open Charts

Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.

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open_in_newview in Open Charts

FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.

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open_in_newview in Open Charts

FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.

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open_in_newview in Open Charts

FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.

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open_in_newview in Open Charts

FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.

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open_in_newview in Open Charts

FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.

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open_in_newview in Open Charts

GraphCast (Google DeepMind): a deep learning-based system developed by Google DeepMind.It is initialised with ECMWF analysis. GraphCast operates at 0.25° resolution.

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open_in_newview in Open Charts

GraphCast (Google DeepMind): a deep learning-based system developed by Google DeepMind.It is initialised with ECMWF analysis. GraphCast operates at 0.25° resolution.

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open_in_newview in Open Charts

GraphCast (Google DeepMind): a deep learning-based system developed by Google DeepMind.It is initialised with ECMWF analysis. GraphCast operates at 0.25° resolution.

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open_in_newview in Open Charts
This dataset provides aerosol optical depths and aerosol-radiation radiative effects for four different aerosol origins: anthropogenic, mineral dust, marine, and land-based fine-mode natural aerosol. The latter mostly consists of biogenic aerosols.

calendar_today Interval/period: Wed, 01/01/2003 - Sun, 12/31/2017

This dataset provides aerosol optical depths and aerosol-radiation radiative effects for four different aerosol origins: anthropogenic, mineral dust, marine, and land-based fine-mode natural aerosol. The latter mostly consists of biogenic aerosols.

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This dataset provides geographical distributions of the radiative forcing (RF) by key atmospheric constituents. The radiative forcing estimates are based on the CAMS reanalysis and additional model simulations and are provided separately for...

carbon dioxide
methane
tropospheric ozone
stratospheric ozone
interactions between anthropogenic aerosols and radiation
interactions between anthropogenic aerosols and clouds

calendar_today Interval/period: Wed, 01/01/2003 - Sun, 12/31/2017

This dataset provides geographical distributions of the radiative forcing (RF) by key atmospheric constituents. The radiative forcing estimates are based on the CAMS reanalysis and additional model simulations and are provided separately for...
    - carbon dioxide
    - methane
    - tropospheric ozone
    - stratospheric ozone
    - interactions between anthropogenic aerosols and radiation

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This dataset provides historical values of global, direct and diffuse solar
irradiation, as well as direct normal irradiation, on a latitude/longitude grid
covering land surfaces and coastal areas of Europe, Africa, Oceania, Eastern
South America, the Middle East and South-East Asia. It is created from 15 minute
resolved timeseries at each grid point. These timeseries were calculated by the
CAMS Solar Radiation Time Series Service and use information on aerosol, ozone

calendar_today Interval/period: Sat, 01/01/2005 - Sun, 12/31/2023