Historical AROME Arctic files from the operational numerical weather prodiction model run. The moste recent datasets are also available labelled post-processed or extracted as separate datsets.
Extracted variables based on the latest run of the AROME-Arctic model, without additional post-processing. Data on surface, and selected model and pressure levels. Horizontal data resolution is 2,5km. The forecast is updated 4 times per day. For historical data see https://thredds.met.no/thredds/catalog/aromearcticarchive/catalog.html
Post processed forecasts based on the latest run of the AROME-Arctic model. Parameters like temperature, cloud cover, precipitation and wind have gone through additional post-processing. Horizontal data resolution is 2,5km. The forecast is updated 4 times per day. For historical data see https://thredds.met.no/thredds/catalog/aromearcticarchive/catalog.html
This ocean model is operated at 20km resolution covering the Nordic Seas
and the Arctic Ocean. This specific dataset provides the daily analysis
from the operational model. Only the analysis is provided for historical
periods, the daily forecast with 1 hour resolution is provided as a
separate dataset. Currently the WMS presentation of this dataset is not
supporting the 3D nature.
A numerical model is applied to describe the dynamics of the oceans, such
as sea level variations (tides and storm surge), movements in the water
column (currents) and the salinity and temperature. To simulate the ocean,
a 3-D grid is applied with different sizes, i.e., small grids for fine
scale or detailed calculations, and larger or coarser grids to cover
larger areas (and depth). The model runs on a supercomputer, and provides
forecasts of sea level, currents, salinity and temperature for a
time-range between 66 (2.75 days) and 240 hours (10 days). The model is
run operationally, i.e, in a "24/7/365" environment to provide a 99.5%
stability on a yearly basis. Currents from the model is further applied in
emergency-models that simulates pathways of oil slicks and drifting
objects (Search And Rescue).
The ocean model used is the Regional Ocean Modeling System (ROMS). This is
a three-dimensional, free-surface, terrain-following numerical model that
solve the Reynolds-averaged Navier-Stokes equations using the hydrostatic
and Boussinesq assumptions (Haidvogel et al., 2008).
Haidvogel, D. B., H. Arango, W. P. Budgell, B. D. Cornuelle, E.
Curchitser, E. Di Lorenzo, K. Fennel, W. R. Geyer, A. J. Hermann, L.
Lanerolle, J. Levin, J. C. McWilliams, A. J. Miller, A. M. Moore, T. M.
Powell, A. F. Shchepetkin, C. R. Sherwood, R. P. Signell, J. C. Warner,
and J. Wilkin, Ocean forecasting in terrain-following coordinates:
Formulation and skill assessment of the Regional Ocean Modeling System,
JOURNAL OF COMPUTATIONAL PHYSICS, 227, 3595–3624, 2008.
THIS MODEL IS DISCONTINUED AND NO FORECAST DATA IS AVAILABLE ONLINE.
This ocean model is operated at 20km resolution covering the Nordic Seas
and the Arctic Ocean. This specific dataset provides the hourly forecast
fields from the operational model. For historical purposes, the daily
analysis is provided as another dataset. If for some reason the
historical forecast is required, pleased use the contact information
provided to receive this (manual task).
A numerical model is applied to describe the dynamics of the oceans, such
as sea level variations (tides and storm surge), movements in the water
column (currents) and the salinity and temperature. To simulate the ocean,
a 3-D grid is applied with different sizes, i.e., small grids for fine
scale or detailed calculations, and larger or coarser grids to cover
larger areas (and depth). The model runs on a supercomputer, and provides
forecasts of sea level, currents, salinity and temperature for a
time-range between 66 (2.75 days) and 240 hours (10 days). The model is
run operationally, i.e, in a "24/7/365" environment to provide a 99.5%
stability on a yearly basis. Currents from the model is further applied in
emergency-models that simulates pathways of oil slicks and drifting
objects (Search And Rescue).
The ocean model used is the Regional Ocean Modeling System (ROMS). This is
a three-dimensional, free-surface, terrain-following numerical model that
solve the Reynolds-averaged Navier-Stokes equations using the hydrostatic
and Boussinesq assumptions (Haidvogel et al., 2008).
Haidvogel, D. B., H. Arango, W. P. Budgell, B. D. Cornuelle, E.
Curchitser, E. Di Lorenzo, K. Fennel, W. R. Geyer, A. J. Hermann, L.
Lanerolle, J. Levin, J. C. McWilliams, A. J. Miller, A. M. Moore, T. M.
Powell, A. F. Shchepetkin, C. R. Sherwood, R. P. Signell, J. C. Warner,
and J. Wilkin, Ocean forecasting in terrain-following coordinates:
Formulation and skill assessment of the Regional Ocean Modeling System,
JOURNAL OF COMPUTATIONAL PHYSICS, 227, 3595–3624, 2008.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available satellite data and insitu observations and provides a gridded map. It is a continuation of the previous sea ice chart which basically identified the ice edge.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available insitu observations. This dataset is the predecessor of the gridded ice charts based on satellite data and other sources. This dataset primarily identifies the sea ice edge.
Polar Amplification Model Intercomparison Project (PAMIP)
Institutions: Alfred Wegener Institute
Last metadata update: 2022-11-24T12:36:33Z
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Abstract:
This dataset comprises 8 atmosphere-only experiments of 100 ensemble members each for the coordinated PAMIP (Polar Amplification Model Intercomparison Project) within CMIP6. The following experiments are included: PAMIP 1.1, PAMIP 1.2, PAMIP 1.3, PAMIP 1.4, PAMIP 1.5, PAMIP 1.6, PAMIP 3.1, PAMIP 3.2). With this set the influence of modified sea ice conditions and the influence of modified sea surface temperature conditions on the atmosphere can be investigated. Further information and references can be found here: https://cera-www.dkrz.de/WDCC/ui/cerasearch/cmip6?input=CMIP6.PAMIP.AWI.AWI-CM-1-1-MR
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from BARDUFOSS
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from KONGSOYA
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from HEKKINGEN LH
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from HORNSUND
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from JAN MAYEN
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from NY-ALESUND
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from VERLEGENHUKEN
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
Access: Open
Access: Registered users only (manual approval required)