A Nonhomogeneous Regression-Based Statistical Postprocessing Scheme for Generating Probabilistic Quantitative Precipitation Forecast
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields

Dates

to

Document Data
Library
People
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.
i

A Nonhomogeneous Regression-Based Statistical Postprocessing Scheme for Generating Probabilistic Quantitative Precipitation Forecast

Filetype[PDF-2.86 MB]



Details:

  • Journal Title:
    Journal of Hydrometeorology
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    This paper introduces a new, two-part scheme for postprocessing single-valued precipitation forecast to create probabilistic quantitative precipitation forecast (PQPF). This scheme, herein referred to as the mixed-type nonhomogeneous regression (MNHR), combines the use of logistic regression for estimating rainfall intermittency and nonhomogeneous regression for estimation of additional parameters of the conditional distribution. The performance of MNHR is evaluated relative to operational mixed-type meta-Gaussian distribution (MMGD) and the censored, shifted gamma distribution (CSGD) in postprocessing Global Ensemble Forecast System (GEFS) reforecasts averaged over 25 watersheds in the American River basin in California. The results point to superior performance of MNHR relative to MMGD and CSGD in terms of the skill of postprocessed PQPFs at 24- and 96-h accumulation windows. In addition, it is observed that the performance of CSGD tends to trail behind MNHR and MMGD at least for the 24-h window, though the performance differences tend to narrow at higher forecast amounts and longer lead times. Our analyses suggest that CSGD’s underperformance arises partly from its tendency to inflate the shift parameter estimates, which is pronounced over the study site possibly because of infrequent rainfall occurrence. By contrast, MNHR’s use of logistic regression helps avoid such bias, and its formulation of conditional distribution addresses the lack of skewness of MMGD for higher forecast amounts. Moreover, MHNR-based PQPF exhibits both superior calibration and relatively high sharpness at short lead times and on an unconditional sense, whereas it features lower sharpness relative to the other two suites when conditioned on higher forecast amount. This trade-off between calibration andconditionalsharpness warrants further research.
  • Keywords:
  • Source:
    Journal of Hydrometeorology, 21(10), 2275-2291
  • DOI:
  • ISSN:
    1525-755X;1525-7541;
  • Format:
  • Publisher:
  • Document Type:
  • Funding:
  • Rights Information:
    Other
  • Compliance:
    Library
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files
More +

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.27.1