GHRSST-PP
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The GODAE High Resolution Sea Surface Temperature Pilot Project
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The GHRSST-PP International Project Office is sponsored by ESA and the Met Office

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Applications

Satellite SST measurements are used in many applications as they provide a synoptic view of the dynamic thermal character of the ocean surface. Measurements are fundamentally important to agencies and institutions tasked with the study of climate variability, operational weather and ocean forecasting, military operations, validation and forcing of ocean and atmospheric models, ecosystem assessment, tourismand, fisheries research, amongst many others.

Ocean Forecasting
Modern Ocean Forecasting systems provide a full 4-dimensional decription of the ocean at various vertical and horizontal spatial resolutions. SST data are used as a boundary conditions and in data assimilation schemes within these model systems.
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Research & Development
There is a great deal of R&D taking place by groups both using and producing satellite SST maps. Understanding the impact of diurnal variability and the difference between SSTskin and SSTdepth are key issues for the GHRSST-PP.
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Weather Forecasting
Numerical Weather Prediction Systems require SST as a bottom boundary condition and can, in certain cases, have an impartant impact on the forecasts e.g., fog formation, cyclogenisis, hurricane intensity and storm track forecast, air-sea flux calculations.
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Climate & Seasonal Forecasting
Accurate maps of SST are arguably one of the best climate indicators in their own right. Statistical Seasonal forecasts are based predictors derived from tropical Atlantic and Tropical Pacific SST indeces and an accurate time-series of SST is required to initialise dynamical seasonal forecasts using coupled ocean-atmosphere seasonal prediction models.
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Travel & Tourism
What's the temperature of the sea going to be on the beach at your holiday destination? Find out today using GHRSST-PP data products!
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Todays Data
There are several SST analysis systems running within the framework of GHRSST-PP providing daily L4 gridded data products.
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Craig Donlon | Last updated on 11th October 2005