Ensemble-based targeting experiments during FASTEX: The effect of dropsonde data from the Lear jet

In this study we evaluate the performance of the Ensemble Transform (ET) technique, which is one of several targeting methods used in real time during the Fronts and Atlantic Storm-Track EXperiment (FASTEX). 'Targeted' observations were taken adaptively in those upstream areas identified i...

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Veröffentlicht in:Quarterly journal of the Royal Meteorological Society 1999-10, Vol.125 (561), p.3189-3217
Hauptverfasser: SZUNYOGH, I, TOTH, Z, EMANUEL, KA, BISHOP, CH, SNYDER, C, MORSS, RE, WOOLEN, J, MARCHOK, T
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Sprache:eng
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Zusammenfassung:In this study we evaluate the performance of the Ensemble Transform (ET) technique, which is one of several targeting methods used in real time during the Fronts and Atlantic Storm-Track EXperiment (FASTEX). 'Targeted' observations were taken adaptively in those upstream areas identified in real time as most relevant for improving the initial conditions for forecasts of synoptic-scale storms developing downstream. The upstream areas were identified as regions where the effect of extra observations at a future analysis time could produce the largest decrease in the largest likely forecast error at a preselected later verification time at a given downstream location. The ET technique selects these observational areas out of a large number of possible deployment locations of observational resources via a linear transformation of an ensemble of forecasts. The analysis and forecast effects of special targeted observations associated with seven Intensive Observing Periods (IOPs) during FASTEX were investigated. The most important result of the present study is that the ET technique, based on the National Centers for Environmental Prediction (NCEP) operational global ensemble, was able to identify upstream areas that had significant contribution to the quality of selected future downstream forecast features. Moreover, the technique could reliably distinguish between the areas of greatest contribution. Though the overall impact of the targeted data on forecast quality is positive, there were cases when the extra data degraded the forecasts. Our analysis indicates that large amplification of ensemble perturbations from the targeted area into the verification area is a good indicator of potential forecast improvement.
ISSN:0035-9009
1477-870X
DOI:10.1256/smsqj.56103