Observations of significant wave heights are obtained from the altimetry satellites Jason-1 and Envisat. The accuracy of the significant waveheight observations is on the order of 20 cm. DMI use the observations along the satellite tracks to compare with the operational model forecasts of significant wave height. The forecast error is mapped for the Northwest European Shelf Seas, and mean errors are calculated as a function of wave height, forecast range, and time of year. The comparison is carried out every half year and the results are displayed here.
.........................................
Contact: Jacob L. Høyer
jlh@dmi.dk

Satellite observations of sea surface temperature is currently retrieved from several satellites. The most accurate infrared satellites have an pixel size of 1 km and an accuracy of 0.3 degrees but they are limited by clouds. DMI has developed a statistical method that uses the individual error characteristics to combine satellite observations from about 10 different instruments in an objective interpolation method. The satellite observations include polar orbiting infrared and microwave sensors as well as geostationary satellite observations and are obtained through the Ocean & Sea Ice SAF project and the GHRSST project. One field is produced every day, based upon nighttime observations, and the spatial resolution is 0.03 for the North Sea/Baltic Sea domain and 0.05 degrees for the other domains. To see todays images of Sea Surface Temperature, click here.
.........................................
Contact: Jacob L. Høyer
jlh@dmi.dk

The altimetry satellites Jason-1 and ENVISAT observe the height of the sea surface (SSH) for every 6-7 kilometer directly beneath the satellite. The accuracy of a single observation is better than 4 cm for the open ocean but for shelf and coastal areas like the North Sea and Baltic Sea, the errors on the observations are significantly higher. Several studies have been carried out at DMI to determine how to make best use of the near coastal satellite SSH observations. Specialized treatment has been applied to detide the satellite observations, to reference the satellite and the tide gauge observations and to use a local geoid in the region. The results of these studies show useful information can be extracted from the data with careful data processing and detiding. A multivariate regression model including both tide gauge and satellite observations has shown to perform similar to the storm surge models, in terms of determining the extreme sea level events.
.........................................
Contact: Jacob L. Højer

The OSISAF is part of EUMETSAT's network of Satellite Application Facilities that form a distributed ground segment for the METOP and Meteosat satellites. DMI, with met.no, constitute the high latitude center within the OSISAF and is responsible for the operational production of a range of global sea ice products intended for use in operational meteorological and oceanographic forecas ting. DMI's prime expertise is sea ice products and current operational products include sea ice concentration, edge and type. Th e products are based primarily on atmospherically corrected passive microwave data but can take input from active microwave obser vations when available.
fab@dmi.dk

The prime source of information for operational sea ice services including the North American, the Finnish, the Norwegian and the Greenlandic ice service is satellite SAR data. The high resolution gives accurate information on e.g. ice edge and ice concentration. Image classification techniques ease interpretation.

Read more here.



.........................................
Contact: Matilde Brandt Kreiner

Forward models relate the physical properties of the snow and ice with the microwave thermal emission or backscatter. The models are used:
1) in sensitivity studies, where the microwave signature sensitivity to different physical properties can be simulated,
2) model inversion to derive snow or ice parameters, where the model with its physical input is fitted to a measured signature, or
3) forward modelling to estimate a surface signature using simulated physical input.

Read more here.

.........................................
Contact: Johanne Øelund;