Proactive QC: A Fully Flow-Dependent Quality Control Scheme Based on EFSO
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Proactive QC: A Fully Flow-Dependent Quality Control Scheme Based on EFSO

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  • Journal Title:
    Monthly Weather Review
  • Personal Author:
  • NOAA Program & Office:
    NESDIS (National Environmental Satellite, Data, and Information Service)
  • Description:
    Despite dramatic improvements over the last decades, operational NWP forecasts still occasionally suffer from abrupt drops in their forecast skill. Such forecast skill “dropouts” may occur even in a perfect NWP system because of the stochastic nature of NWP but can also result from flaws in the NWP system. Recent studies have shown that dropouts occur due not to a model’s deficiencies but to misspecified initial conditions, suggesting that they could be mitigated by improving the quality control (QC) system so that the observation-minus-background (O-B) innovations that would degrade a forecast can be detected and rejected. The ensemble forecast sensitivity to observations (EFSO) technique enables for the quantification of how much each observation has improved or degraded the forecast. A recent study has shown that 24-h EFSO can detect detrimental O-B innovations that caused regional forecast skill dropouts and that the forecast can be improved by not assimilating them. Inspired by that success, a new QC method is proposed, termed proactive QC (PQC), that detects detrimental innovations 6 h after the analysis using EFSO and then repeats the analysis and forecast without using them. PQC is implemented and tested on a lower-resolution version of NCEP’s operational global NWP system. It is shown that EFSO is insensitive to the choice of verification and lead time (24 or 6 h) and that PQC likely improves the analysis, as attested to by forecast improvements of up to 5 days and beyond. Strategies for reducing the computational costs and further optimizing the observation rejection criteria are also discussed.
  • Keywords:
  • Source:
    Monthly Weather Review, 145(8), 3331-3354
  • DOI:
  • ISSN:
    0027-0644;1520-0493;
  • Format:
    PDF
  • Publisher:
    American Meteorological Society
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA14NES4320003
  • Rights Information:
    Other
  • Compliance:
    Library
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