How Should a Numerical Weather Prediction Be Used: Full Field or Anomaly? A Conceptual Demonstration with a Lorenz Model

Details

• Journal Title:
  Atmosphere
• Personal Author:
  Du, Jun ; Deng, Guo
• NOAA Program & Office:
  NCEP (National Centers for Environmental Prediction) ; NWS (National Weather Service)
• Description:
  A forecast from a numerical weather prediction (NWP) model can be decomposed into model climate and anomaly. Each part contributes to forecast error. To avoid errors from model climate, an anomaly, rather than a full field, should be used in a model. Model climate is replaced by the observed climate to reconstruct a new forecast for application. Using a Lorenz model, which has similar error characteristics to an NWP model, the following results were obtained. (a) The new anomaly-based method can significantly and steadily increase forecast accuracy throughout the entire forecast period (28 model days). On average, the total forecast error was reduced ~25%, and the correlation was increased by ~100–200%. The correlation improvement increases with the increasing of forecast length. (b) The method has different impacts on different types of error. Bias error was almost eliminated (over 90% in reduction). However, the change in flow-dependent error was mixed: a slight reduction (~5%) for model day 1–14 forecasts and increase (~15%) for model day 15–28 forecasts on average. The larger anomaly forecast error leads to the worsening of flow-dependent error. (c) Bias error stems mainly from model climate prediction, while flow-dependent error is largely associated with anomaly forecast. The method works more effectively for a forecast that has larger bias and smaller flow-dependent error. (d) A more accurate anomaly forecast needs to be constructed relative to model climate rather than observed climate by taking advantage of cancelling model systematic error (i.e., perfect-model assumption). In principle, this approach can be applicable to any model-based prediction.
• Keywords:
  Atmospheric Science Environmental Science (miscellaneous)
• Source:
  Atmosphere, 13(9), 1487
• DOI:
  https://doi.org/10.3390/atmos13091487
• ISSN:
  2073-4433
• Format:
  PDF
• Publisher:
  MDPI AG
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Library
• Main Document Checksum:
  urn:sha-512:c2b6cb2cd53bdafeddf4752b0fb497b608eee143294b8cc38454ff7a140ebcea8d8b1000a41c5f8924b4e0083c0b4caa01e73420cb24c1a86829a49961fc3d80
• Download URL:
  https://repository.library.noaa.gov/view/noaa/63711/noaa_63711_DS1.pdf
• File Type:
  [PDF - 9.40 MB ]