Details:

Journal Title:
Weather and Forecasting
Personal Author:
Gasperoni, Nicholas A. ; Wang, Xuguang ; Wang, Yongming ; Li, Tsung-Han
Gasperoni, Nicholas A. ; Wang, Xuguang ; Wang, Yongming ; Li, Tsung-Han Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research)
Description:
Multiscale valid time shifting (VTS) was explored for a real-time convection-allowing ensemble (CAE) data assimilation (DA) system featuring hourly assimilation of conventional in situ and radar reflectivity observations, developed by the Multiscale Data Assimilation and Predictability Laboratory. VTS triples the base ensemble size using two subensembles containing member forecast output before and after the analysis time. Three configurations were tested with 108-member VTS-expanded ensembles: VTS for individual mesoscale conventional DA (ConVTS) or storm-scale radar DA (RadVTS) and VTS integrated to both DA components (BothVTS). Systematic verification demonstrated that BothVTS matched the DA spread and accuracy of the best-performing individual component VTS. The 10-member forecasts showed BothVTS performs similarly to ConVTS, with RadVTS having better skill in 1-h precipitation at forecast hours 1–6, while Both/ConVTS had better skill at later hours 7–15. An objective splitting of cases by 2-m temperature cold bias revealed RadVTS was more skillful than Both/ConVTS out to hour 10 for cold-biased cases, while BothVTS performed best at most hours for less-biased cases. A sensitivity experiment demonstrated improved performance of BothVTS when reducing the underlying model cold bias. Diagnostics revealed enhanced spurious convection of BothVTS for cold-biased cases was tied to larger analysis increments in temperature than moisture, resulting in erroneously high convective instability. This study is the first to examine the benefits of a multiscale VTS implementation, showing that BothVTS can be utilized to improve the overall performance of a multiscale CAE system. Further, these results underscore the need to limit biases within a DA and forecast system to best take advantage of VTS analysis benefits.
Keywords:
[+]
Atmospheric Science
Source:
Weather and Forecasting, 38(11), 2343-2362
DOI:
https://doi.org/10.1175/waf-d-23-0096.1
ISSN:
0882-8156;1520-0434;
Format:
PDF
Publisher:
American Meteorological Society
Document Type:
Journal Article
Funding:
Grant no. NA19OAR4590138 ; Grant no. NA19OAR4590231
Grant no. NA19OAR4590138 ; Grant no. NA19OAR4590231 Less -
Rights Information:
Other
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:44a58e280b9a02b560c08394b1b3e173e1087c1f304f2f560fb89a481bad6dd3
Download URL:
https://repository.library.noaa.gov/view/noaa/60114/noaa_60114_DS1.pdf
File Type:

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