The Effects of Moist Physics on the Singular Vector Downscaling Initial Perturbations in Convection-Permitting Ensemble Prediction.
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| Title: | The Effects of Moist Physics on the Singular Vector Downscaling Initial Perturbations in Convection-Permitting Ensemble Prediction. |
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| Authors: | Wang, Jingzhuo1,2,3 (AUTHOR), Zhang, Hanbin4 (AUTHOR) hbzhang@ium.cn, Liu, Yongzhu1,2,3 (AUTHOR), Qi, Qianqian1,2,3 (AUTHOR), Ma, Yanan5 (AUTHOR) |
| Source: | Journal of Applied Meteorology & Climatology. Dec2025, Vol. 64 Issue 12, p1909-1929. 21p. |
| Subjects: | Condensation, Cumulus clouds, Forced convection, Perturbation theory, Downscaling (Climatology), Statistical ensembles |
| Abstract: | To reveal the impacts of linearized moist physical processes, especially humidity terms, on singular vector (SV) structures and the associated prediction skills for the convection-permitting ensemble prediction system (CPEPS), four groups of experiments with different combinations of dry physical processes, large-scale condensation, and cumulus deep convection were designed. The results revealed that 1) the linearized large-scale condensation scheme obviously enhances moist energy norms in the troposphere and has considerable effects on potential energy norms, whereas cumulus deep convection affects moist and potential energy norms at lower levels at initial times. Both schemes lead to fast SV growth rates. 2) Large-scale condensation enhances the perturbation magnitudes and energy spectra of the mixing ratio across the troposphere and at almost all scales but decreases the perturbations of zonal wind and potential temperature at high and low levels. However, cumulus deep convection mainly affects mixing ratio perturbations at lower levels. 3) Large-scale condensation improves the spread–skill relationships and probabilistic forecasts for the mixing ratio at early hours and precipitation at most hours when added to dry processes. Additionally, cumulus deep convection slightly improves the spread–skill relationships for the mixing ratio at lower levels and rainstorm and generally leads to better probabilistic skills for precipitation when added to dry processes. 4) The overall effects of cumulus deep convection are smaller than those of the large-scale condensation scheme. These findings highlight the roles of moist SVs in enhancing the mixing ratio initial perturbations and improving precipitation forecasts within the CPEPS. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | To reveal the impacts of linearized moist physical processes, especially humidity terms, on singular vector (SV) structures and the associated prediction skills for the convection-permitting ensemble prediction system (CPEPS), four groups of experiments with different combinations of dry physical processes, large-scale condensation, and cumulus deep convection were designed. The results revealed that 1) the linearized large-scale condensation scheme obviously enhances moist energy norms in the troposphere and has considerable effects on potential energy norms, whereas cumulus deep convection affects moist and potential energy norms at lower levels at initial times. Both schemes lead to fast SV growth rates. 2) Large-scale condensation enhances the perturbation magnitudes and energy spectra of the mixing ratio across the troposphere and at almost all scales but decreases the perturbations of zonal wind and potential temperature at high and low levels. However, cumulus deep convection mainly affects mixing ratio perturbations at lower levels. 3) Large-scale condensation improves the spread–skill relationships and probabilistic forecasts for the mixing ratio at early hours and precipitation at most hours when added to dry processes. Additionally, cumulus deep convection slightly improves the spread–skill relationships for the mixing ratio at lower levels and rainstorm and generally leads to better probabilistic skills for precipitation when added to dry processes. 4) The overall effects of cumulus deep convection are smaller than those of the large-scale condensation scheme. These findings highlight the roles of moist SVs in enhancing the mixing ratio initial perturbations and improving precipitation forecasts within the CPEPS. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15588424 |
| DOI: | 10.1175/JAMC-D-25-0102.1 |
