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Effect of preceding soil moisture-snow cover anomalies around Turan Plain on June precipitation over the southern Yangtze River valley.
- Source :
-
Atmospheric Research . Dec2021, Vol. 264, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- This study investigates precursory signals of the June precipitation over the southern Yangtze River valley (SYRV). It is found that the synergistic anomalies of the Turan Plain soil moisture and northern Iranian Plain snow cover (TPSM-IPSC) during April can modulate the June SYRV precipitation. Through the persistence/memory effect of soil moisture anomalies, lower soil moisture around the Turan Plain-Iranian Plain region can maintain from April to June. Because of drier soil (i.e., lower soil moisture), higher surface air temperature (SAT) appears over the Turan Plain during June. The higher SAT anomaly stimulates anomalous upward motion and associated overlying and downstream atmospheric circulation anomalies through modulating the downstream dispersion of Rossby wave energy. As a part of these atmospheric circulation anomalies, the blocking-like anomaly to the west of the Okhotsk Sea facilitates more June precipitation over the SYRV. Additionally, June SYRV precipitation is significantly correlated with sea surface temperature (SST) anomalies in the tropical eastern Pacific (TEP) during the preceding winter. The TPSM-IPSC can compensate for the defect of prediction using the TEP SST (i.e., ENSO) signal in recent years since the former (latter) shows a strengthened (weakened) relationship with SYRV precipitation recently. Considering jointly the traditional pacific SST and new TPSM-IPSC precursors, we establish a physics-based statistical prediction model, which shows a good skill in predicting June SYRV precipitation. • Precursory signals of the June southern Yangtze River valley precipitation was found. • Physical process linking April TPSM-IPSC and June SYRV precipitation was revealed. • A physics-based statistical prediction model was established. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01698095
- Volume :
- 264
- Database :
- Academic Search Index
- Journal :
- Atmospheric Research
- Publication Type :
- Academic Journal
- Accession number :
- 153285426
- Full Text :
- https://doi.org/10.1016/j.atmosres.2021.105853