The impact of targeted observations made during the Greenland Flow Distortion Experiment
The impact of targeted sonde observations on the 1-3 day forecasts for northern Europe is evaluated using the Met Office four-dimensional variational data assimilation scheme and a 24 km gridlength limited-area version of the Unified Model (MetUM). The targeted observations were carried out during F...
| Published in: | Quarterly Journal of the Royal Meteorological Society |
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| Main Authors: | , , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | https://ueaeprints.uea.ac.uk/id/eprint/24594/ https://ueaeprints.uea.ac.uk/id/eprint/24594/1/irvine_etal_impact_targeted_obs_QJRMS_2009.pdf https://doi.org/10.1002/qj.499 |
| Summary: | The impact of targeted sonde observations on the 1-3 day forecasts for northern Europe is evaluated using the Met Office four-dimensional variational data assimilation scheme and a 24 km gridlength limited-area version of the Unified Model (MetUM). The targeted observations were carried out during February and March 2007 as part of the Greenland Flow Distortion Experiment, using a research aircraft based in Iceland. Sensitive area predictions using either total energy singular vectors or an ensemble transform Kalman filter were used to predict where additional observations should be made to reduce errors in the initial conditions of forecasts for northern Europe. Targeted sonde data was assimilated operationally into the MetUM. Hindcasts show that the impact of the sondes was mixed. Only two out of the five cases showed clear forecast improvement; the maximum forecast improvement seen over the verifying region was approximately 5% of the forecast error 24 hours into the forecast. These two cases are presented in more detail: in the first the improvement propagates into the verification region with a developing polar low; and in the second the improvement is associated with an upper-level trough. The impact of cycling targeted data in the background of the forecast (including the memory of previous targeted observations) is investigated. This is shown to cause a greater forecast impact, but does not necessarily lead to a greater forecast improvement. Finally, the robustness of the results is assessed using a small ensemble of forecasts. |
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