the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sea ice reduction in the Barents-Kara Sea enhances June precipitation in the Yangtze River basin
Abstract. This study investigates the influence of June sea surface temperature (SST) and sea ice in the Barents-Kara Sea (BKS) on concurrent rainfall variability in the Yangtze River basin from 1982 to 2021 using both observational data and numerical experiments. The observed decrease in BKS sea ice and the corresponding increase in SST during June aligns with enhanced precipitation in the Yangtze River basin on the interannual timescale. The BKS thermal forcing induces an equivalent barotropic Rossby wave train in the middle and upper troposphere, which propagates southeastward to the Northwest Pacific (NWP). This Rossby wave train features two positive centers over the BKS and NWP, and one negative center above the Baikal Lake. The strengthened NWP subtropical high and upper-level westerly jet contribute to increased rainfall in the Yangtze River basin by enhancing moisture transport and anomalous ascending motions. These findings provide important implications for predicting summer rainfall in East Asia.
- Preprint
(2511 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 30 Oct 2024)
-
RC1: 'Comment on egusphere-2024-2417', Anonymous Referee #1, 01 Oct 2024
reply
This study examines the relationship between June sea surface temperature (SST) and sea ice in the Barents-Kara Sea (BKS) and rainfall variability in the Yangtze River basin from 1982 to 2021. It finds that the observed decline in sea ice and rise in SST over the BKS region correlate with increased precipitation in the Yangtze River basin on an interannual timescale. The research identifies a barotropic Rossby wave train triggered by BKS thermal forcing, which propagates southeastward, contributing to enhanced rainfall through the strengthening of the subtropical high over the northwest Pacific region. These results have significant implications for summer rainfall predictions in East Asia. The paper is well organized and I have some comments and questions.
Review Comments:
- Figure 1a displays regions of white within the SIC correlation coefficient map. These areas could either represent absence of sea ice in June or result from low standard deviation values. Given the potential for minimal or no sea ice presence, it would be helpful if the authors elucidated the rationale behind extending the study area beyond the Kara Sea. A more comprehensive explanation is warranted. In addition, delete either one colorbar in Fig.1a and Fig.1b since they are same.
- The manuscript provides an extensive description of radiation flux; however, the definitions of the directional components within this context lacks clarity. It is advisable for the authors to incorporate precise definitions for these components to enhance understanding.
- Figure 6 presents the results from the model simulations, utilizing the second principal component (PC2) of the EOF analysis, which indicates the presence of a wave-like pattern. This prompts two critical inquiries: Firstly, which EOF mode in the observations corresponds to the ‘+-+’ pattern? Secondly, do the model simulations align with the observations?
- In Figure 5c, the units of the arrows should be specified as kg m⁻¹ s⁻¹. It is advisable for the authors to amend this notation in the figure accordingly.
- The manuscript states, "However, the intensified net heat flux from the atmosphere to the ocean in the BKS region is not a direct cause of sea ice melting, but rather a consequence of decreased sea ice concentration." It is recommended that the authors further elucidate the causal relationship between these phenomena.
Citation: https://doi.org/10.5194/egusphere-2024-2417-RC1
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
75 | 14 | 50 | 139 | 1 | 1 |
- HTML: 75
- PDF: 14
- XML: 50
- Total: 139
- BibTeX: 1
- EndNote: 1
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1