A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application
Abstract
Abstract Data assimilation (DA) at mesoscales is important for severe weather forecasts, yet the techniques of data assimilation at this scale remain a challenge. This study introduces dynamical constraints in the Gridpoint Statistical Interpolation (GSI) three-dimensional ensemble variational (3D-EnVar) data assimilation algorithm to enable the use of high-resolution surface observations of precipitation to improve atmospheric analysis at mesoscales. The constraints use the conservations of mass and moisture. Mass constraint suppresses the unphysical high-frequency oscillation, while moisture conservation constrains the atmospheric states to conform with the observed high-resolution precipitation. We show that the constrained data assimilation (CDA) algorithm significantly reduced the spurious residuals of the mass and moisture budgets compared to the original data assimilation (ODA). A case study is presented for a squall line over the Southern Great Plains on 20 May 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E) of the Atmospheric Radiation Measurement (ARM) program by using ODA or CDA analysis as initial condition of forecasts. The state variables, and the location and intensity of the squall line are better simulated in the CDA experiment. Results show how surface observation of precipitation can be used to improve atmospheric analysis through data assimilation by using the dynamical constraints ofmore »
- Authors:
-
[1];
- a School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York
- Publication Date:
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1825563
- Resource Type:
- Published Article
- Journal Name:
- Monthly Weather Review
- Additional Journal Information:
- Journal Name: Monthly Weather Review Journal Volume: 149 Journal Issue: 10; Journal ID: ISSN 0027-0644
- Publisher:
- American Meteorological Society
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Wang, Jia, and Zhang, Minghua. A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application. United States: N. p., 2021.
Web. doi:10.1175/MWR-D-21-0052.1.
Wang, Jia, & Zhang, Minghua. A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application. United States. https://doi.org/10.1175/MWR-D-21-0052.1
Wang, Jia, and Zhang, Minghua. Fri .
"A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application". United States. https://doi.org/10.1175/MWR-D-21-0052.1.
@article{osti_1825563,
title = {A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application},
author = {Wang, Jia and Zhang, Minghua},
abstractNote = {Abstract Data assimilation (DA) at mesoscales is important for severe weather forecasts, yet the techniques of data assimilation at this scale remain a challenge. This study introduces dynamical constraints in the Gridpoint Statistical Interpolation (GSI) three-dimensional ensemble variational (3D-EnVar) data assimilation algorithm to enable the use of high-resolution surface observations of precipitation to improve atmospheric analysis at mesoscales. The constraints use the conservations of mass and moisture. Mass constraint suppresses the unphysical high-frequency oscillation, while moisture conservation constrains the atmospheric states to conform with the observed high-resolution precipitation. We show that the constrained data assimilation (CDA) algorithm significantly reduced the spurious residuals of the mass and moisture budgets compared to the original data assimilation (ODA). A case study is presented for a squall line over the Southern Great Plains on 20 May 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E) of the Atmospheric Radiation Measurement (ARM) program by using ODA or CDA analysis as initial condition of forecasts. The state variables, and the location and intensity of the squall line are better simulated in the CDA experiment. Results show how surface observation of precipitation can be used to improve atmospheric analysis through data assimilation by using the dynamical constraints of mass and moisture conservations.},
doi = {10.1175/MWR-D-21-0052.1},
journal = {Monthly Weather Review},
number = 10,
volume = 149,
place = {United States},
year = {Fri Oct 01 00:00:00 EDT 2021},
month = {Fri Oct 01 00:00:00 EDT 2021}
}
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