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Content archived on 2024-05-24
Integrated observing and modeling of th arctic sea ice and atmosphere

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Monitoring the water cycle from space

Among the most poorly observed components of the Earth's climate system is the atmospheric water vapour and its variations on seasonal to annual time scales. Accurate water vapour estimates, based on satellite-derived measurements from microwave radiometers, can offer the possibility to support more sophisticated weather prediction models.

The importance of water to the Earth's climate and the millions of species living on the Earth is enormous. Gaseous water, in the form of atmospheric vapour, is the primary greenhouse gas, helping to maintain the terrestrial atmosphere within a temperature range conducive to life as we know it. On the other hand, evaporation of water involves the absorption of energy, which is later released to the atmosphere as the resultant water vapour condenses and powers atmospheric circulation. Essential to understanding global climate change and improving weather forecasts is the gathering of basic data such as temperature, pressure, the distribution of water vapour and other active constituents. Radiation at microwave frequencies penetrates clouds and provides an all-weather measurement capability for these parameters. Realising the possibilities of microwave remote sensing, researchers at the University of Bremen developed an advanced algorithm for radiances measured by the new generation of polar orbiting National Oceanographic and Atmospheric Administration (NOAA) satellites. The algorithm is configured to retrieve the total column water vapour (TCWV) over the Arctic regions from microwave remote sensing data taken by the Advanced Microwave Sounding unit (AMSU-B). Due to generally cold temperatures, atmospheric water vapour concentrations in these regions are quite low, allowing heat energy from the surface to escape through the atmosphere more easily than in other regions. For optimal water vapour profiling, auxiliary data, such as estimates of sea ice emissivities, were used when available to enhance the algorithm's standalone performance. The derived large-scale maps of the total water vapour, covering the polar regions have been successfully integrated into numerical climate and weather prediction models within the scope of the IOMASA project. Taking the assimilation of water vapour data a step further, project partners are looking to exploit them in regional models for investigating the global water cycle variations.

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