{"title":"Origin of the 30–60-day intraseasonal oscillation of streamflow in source region of Yellow River in China: a perspective of the atmospheric signals from mid-high latitude","authors":"Lun Li, Congwen Zhu, Xiangde Xu, Ziyan Zheng, Shuangmei Ma, Wanyi Sun","doi":"10.1186/s40562-024-00348-4","DOIUrl":"https://doi.org/10.1186/s40562-024-00348-4","url":null,"abstract":"Streamflow in source region of Yellow River (SRYR) matters with regard to the adjacent and downstream water resources. Intraseasonal oscillation (ISO) in the streamflow in SRYR is of great significance to the sub-seasonal prediction of streamflow in SRYR, but is unknown. Here, we first report a 30–60-day ISO in the streamflow in SRYR, which is regulated by the atmospheric 30–60-day ISO at mid-high latitude over North Eurasia. The 30–60-day ISO in atmosphere is featured by a Rossby wavetrain, and the wave energy propagates southward onto the TP, which causes anomalous wind response over TP. The leading anomalous high (low) with anti-cyclonic (cyclonic) wind anomalies over the TP favors dry (wet) air in lower troposphere in SRYR, via enhancing the water vapor divergence (convergence). Dry (wet) air always results in strong (weak) evaporation from the Yellow River, which causes the later streamflow valley (peak) and thereby the 30–60-day ISO in the streamflow in SRYR.","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The simulation of the Indo-Pacific warm pool SST warming trend in CMIP5 and CMIP6","authors":"Wenrong Bai, Hailong Liu, Pengfei Lin, Hongyan Shen","doi":"10.1186/s40562-024-00346-6","DOIUrl":"https://doi.org/10.1186/s40562-024-00346-6","url":null,"abstract":"This paper evaluates Indo-Pacific warm pool (IPWP) sea surface temperature (SST) warming biases of Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. The IPWP warming trend in the CMIP5 multi-model ensemble (MME) is closer to observation than in CMIP6 MME, but the IPWP expanding trend is the opposite. There is no qualitative improvement in the simulation of IPWP warming from CMIP5 to CMIP6. In addition, four metrics were used to investigate the performance of Indo-Pacific region warming trends in all models. CMIP6 models perform better than CMIP5 with smaller root mean square error and bias in MME and higher skill scores in MME and top models, which is tightly linked to their better performance in simulating associated physical processes in CMIP6 models. IPWP warming biases are mainly attributed to the combined effects of positive atmospheric process biases and negative ocean dynamics term biases. The positive atmospheric process biases are primarily related to the shortwave radiation and latent heat flux from atmospheric forcing, the latter of which can be attributed to the biases in surface wind fields. Compared with CMIP5 models, the IPWP warming simulated by CMIP6 models is weaker, related to the less robust atmospheric processes and the shallower thermocline anomalies simulated by CMIP6.","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141502476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhongqiang Sun, Shuangyue Lin, Guangqun Wang, Longlong Liu, Mengqi Wang
{"title":"Sedimentary evolution pattern influenced by sequence stratigraphy: a case study of the Nanpu Sag, Bohai Bay Basin, China","authors":"Zhongqiang Sun, Shuangyue Lin, Guangqun Wang, Longlong Liu, Mengqi Wang","doi":"10.1186/s40562-024-00345-7","DOIUrl":"https://doi.org/10.1186/s40562-024-00345-7","url":null,"abstract":"Identifying and characterizing sedimentary evolution patterns are crucial for assessing the distributions of source and reservoir rocks, which are fundamental to hydrocarbon exploration. This study analyzed the stratigraphic sequence, lithological characteristics, sedimentary lithofacies, individual well sedimentary sequences, and seismic reflection properties. The analysis revealed six fourth-order sequences, including progradational and regressive sequences, indicative of water level changes. The sediment sources for the second and third sub-members of the Eocene Shahejie Formation's third member (Es32+3) in the Nanpu Sag were identified as the Baigezhuang and Xinanzhuang Uplifts. Predominantly, the sandstones are lithic arkose and feldspathic litharenite, both of which exhibit low compositional and structural maturity. Notably, 22 lithofacies and 8 lithofacies associations suggest fan delta processes. This study identified three fundamental seismic reflection package reflection types. These lithofacies associations, sedimentary sequences, and seismic reflections serve as critical indicators for determining sedimentary environments. The results from the sedimentary facies analysis indicate that the Es32+3 Formation developed fan delta deposits, controlled by the sequence of the sedimentary evolution pattern. The potential of these fan delta sediments to form oil and gas reservoirs is significant. Therefore, precise characterization of the sedimentary evolution pattern is essential for a comprehensive understanding of basin dynamics and hydrocarbon potential.","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141502477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Masuda, Daisuke Sugawara, An-Chi Cheng, A. Suppasri, Yoshinori Shigihara, Shuichi Kure, Fumihiko Imamura
{"title":"Modeling the 2024 Noto Peninsula earthquake tsunami: implications for tsunami sources in the eastern margin of the Japan Sea","authors":"H. Masuda, Daisuke Sugawara, An-Chi Cheng, A. Suppasri, Yoshinori Shigihara, Shuichi Kure, Fumihiko Imamura","doi":"10.1186/s40562-024-00344-8","DOIUrl":"https://doi.org/10.1186/s40562-024-00344-8","url":null,"abstract":"","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141337879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Potential for tsunami detection via CCTV cameras in northeastern Toyama Prefecture, Japan, following the 2024 Noto Peninsula earthquake","authors":"Tomoki Shirai, Yota Enomoto, Keisuke Haga, Tatsuhiko Tokuta, Taro Arikawa, Nobuhito Mori, Fumihiko Imamura","doi":"10.1186/s40562-024-00343-9","DOIUrl":"https://doi.org/10.1186/s40562-024-00343-9","url":null,"abstract":"This study explored closed-circuit television (CCTV) networks in northeastern Toyama Prefecture, Japan, as a new data source for tsunami detection following the 2024 Noto Peninsula earthquake. We analyzed CCTV footage and extracted time-series water level fluctuations at Yokoyama, Shimoiino, and Ekko. Spectral analysis of these waveforms revealed several long-period peaks (more than 100 s) in power spectral density (PSD), suggesting the presence of tsunami components. Notably, relatively large PSD peaks at approximately 5–10 min were observed at all CCTV locations in this study and at offshore wave observation points (Tanaka and Toyama). At Yokoyama, a maximum run-up of approximately 3 m was confirmed around 16:28. Although water level fluctuations at Shimoiino and Ekko were detected, identifying tsunami components proved challenging due to their small magnitude compared to other wave components. Despite these challenges, this study demonstrates the potential of CCTV networks for tsunami detection, and further research is needed to achieve real-time detection.","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141259603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ke-Sheng Cheng, Gwo‑Hsing Yu, Yuan-Li Tai, Kuo-Chan Huang, Sheng‑Fu Tsai, Dong‑Hong Wu, Yun-Ching Lin, Ching-Teng Lee, Tzu-Ting Lo
{"title":"Hypothesis testing for performance evaluation of probabilistic seasonal rainfall forecasts","authors":"Ke-Sheng Cheng, Gwo‑Hsing Yu, Yuan-Li Tai, Kuo-Chan Huang, Sheng‑Fu Tsai, Dong‑Hong Wu, Yun-Ching Lin, Ching-Teng Lee, Tzu-Ting Lo","doi":"10.1186/s40562-024-00341-x","DOIUrl":"https://doi.org/10.1186/s40562-024-00341-x","url":null,"abstract":"A hypothesis testing approach, based on the theorem of probability integral transformation and the Kolmogorov–Smirnov one-sample test, for performance evaluation of probabilistic seasonal rainfall forecasts is proposed in this study. By considering the probability distribution of monthly rainfalls, the approach transforms the tercile forecast probabilities into a forecast distribution and tests whether the observed data truly come from the forecast distribution. The proposed approach provides not only a quantitative measure for performance evaluation but also a cumulative probability plot for insightful interpretations of forecast characteristics such as overconfident, underconfident, mean-overestimated, and mean-underestimated. The approach has been applied for the performance evaluation of probabilistic season rainfall forecasts in northern Taiwan, and it was found that the forecast performance is seasonal dependent. Probabilistic seasonal rainfall forecasts of the Meiyu season are likely to be overconfident and mean-underestimated, while forecasts of the winter-to-spring season are overconfident. A relatively good forecast performance is observed for the summer season.","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141172275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Holocene loess in the Himalayas piedmont of southeastern Nepal","authors":"Edgardo M. Latrubesse, Abang M. S. Nugraha","doi":"10.1186/s40562-024-00338-6","DOIUrl":"https://doi.org/10.1186/s40562-024-00338-6","url":null,"abstract":"","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ping-Yu Chang, Jordi Mahardika Puntu, D. Lin, H. H. Amania, Wen-Shan Chen, Andrew Tien-shun Lin
{"title":"Application of machine learning and resistivity measurements for 3D apparent geological modeling in the Yilan plain, Taiwan, at the SW Tip of the Okinawa trough","authors":"Ping-Yu Chang, Jordi Mahardika Puntu, D. Lin, H. H. Amania, Wen-Shan Chen, Andrew Tien-shun Lin","doi":"10.1186/s40562-024-00339-5","DOIUrl":"https://doi.org/10.1186/s40562-024-00339-5","url":null,"abstract":"","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141120982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effects of variations in po river discharge on physical water characteristics and chlorophyll-a levels in the gulf of manfredonia","authors":"Javad Babagolimatikolaei","doi":"10.1186/s40562-024-00342-w","DOIUrl":"https://doi.org/10.1186/s40562-024-00342-w","url":null,"abstract":"","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141122899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Downscaling Taiwan precipitation with a residual deep learning approach","authors":"Li-Huan Hsu, Chou-Chun Chiang, Kuan-Ling Lin, Hsin-Hung Lin, Jung-Lien Chu, Yi-Chiang Yu, Chin-Shyurng Fahn","doi":"10.1186/s40562-024-00340-y","DOIUrl":"https://doi.org/10.1186/s40562-024-00340-y","url":null,"abstract":"In response to the growing demand for high-resolution rainfall data to support disaster prevention in Taiwan, this study presents an innovative approach for downscaling precipitation data. We employed a hierarchical architecture of Multi-Scale Residual Networks (MSRN) to downscale rainfall from a coarse 0.25-degree resolution to a fine 0.0125-degree resolution, representing a substantial challenge due to a resolution increase of over 20 times. Our results demonstrate that the hierarchical MSRN outperforms both the one-step MSRN and linear interpolation methods when reconstructing high-resolution daily rainfall. It surpasses the linear interpolation method by 15.1 and 9.1% in terms of mean absolute error and root mean square error, respectively. Furthermore, the hierarchical MSRN excels in accurately reproducing high-resolution rainfall for various rainfall thresholds, displaying minimal biases. The threat score (TS) highlights the hierarchical MSRN's capability to replicate extreme rainfall events, achieving TS scores exceeding 0.54 and 0.46 at rainfall thresholds of 350 and 500 mm per day, outperforming alternative methods. This method is also applied to an operational global model, the ECMWF’s daily rainfall forecasts over Taiwan. The evaluation results indicate that our approach is effective at improving rainfall forecasts for thresholds greater than 100 mm per day, with more significant improvement for the 1- to 3-day lead forecast. This approach also offers a realistic visual representation of fine-grained rainfall distribution, showing promise for making significant contributions to disaster preparedness and weather forecasting in Taiwan.","PeriodicalId":48596,"journal":{"name":"Geoscience Letters","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140935867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}