Deliverable No. 4.1 Initial assessment of the added value of observations in existing long time-series datasets – guidance for dedicated observing system experiments
The assessment of state-of-the-art long-term datasets, such as analyses and reanalyses, and short-range weather forecasts was carried out for Arctic regions. It was demonstrated that these datasets can be used for understanding the Arctic climate system variability. It was shown that the quality of...
| Main Authors: | , , , |
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| Format: | Report |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://zenodo.org/record/3567836 https://doi.org/10.5281/zenodo.3567836 |
| Summary: | The assessment of state-of-the-art long-term datasets, such as analyses and reanalyses, and short-range weather forecasts was carried out for Arctic regions. It was demonstrated that these datasets can be used for understanding the Arctic climate system variability. It was shown that the quality of (re)analyses in Arctic regions has increased over the last years, despite the challenges related with the modelling, observation usage and data assimilation encountered in Arctic regions. This further indicates that Numerical Weather Prediction systems can be used for numerical experimentation aimed at informing the design of future observing systems in the Arctic. The use of atmospheric observations in the Arctic region was further analysed for the ECMWF NWP system. The analysis highlights that for global NWP, the polar regions are a particularly data-rich area in terms of satellite sounding observations from polar-orbiting satellites, whereas conventional observations are sparse north of 70N. However, the use of the satellite radiances is hampered during the winter period due to problems over snow and sea-ice in the forward modelling of the satellite radiances and cloud detection, combined with potentially larger errors in the forecast model. There is evidence of considerable bias, originating from the forecast model (especially around 200 hPa), the observation operator for microwave radiances (especially for surface-sensitive radiances over snow and sea-ice), and the cloud screening applied to infrared radiances. As these biases are not accounted for during the assimilation, biases in the resulting analyses are very likely in polar regions. The crucial role of conventional observations in identifying these biases has been highlighted. In addition, our analysis shows that background errors used in the analysis over the Arctic are likely to be under- estimated for the lower troposphere and the upper-troposphere lower-stratosphere. To improve the use of satellite data in the troposphere, improvements in the forward ... |
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