Pub Date : 2024-10-23DOI: 10.1038/s41612-024-00809-9
Jinhui Xie, Pang-Chi Hsu, June-Yi Lee, Lu Wang, Andrew G. Turner
In August 2022, Pakistan experienced unprecedented monsoon rains, leading to devastating floods and landslides affecting millions. While previous research has mainly focused on the contributions of seasonal and synoptic anomalies, this study elucidates the dominant influences of tropical and extratropical intraseasonal oscillations on both the occurrence and subseasonal prediction of this extreme rainfall event. Our scale-decomposed moisture budget analysis revealed that intense rainfall in Pakistan was triggered and sustained by enhanced vertical moisture transport anomalies, primarily driven by interactions between intraseasonal circulation anomalies and the prevailing background moisture field when tropical and mid-latitude systems coincided over Pakistan. Evaluation of subseasonal-to-seasonal prediction models further highlighted the critical role of tropical intraseasonal modes in causing this extreme rainfall event in Pakistan. Models that accurately predicted northward-propagating intraseasonal convection with a forecast lead time of 8–22 days demonstrated good skill in predicting the extreme event over Pakistan.
{"title":"Tropical intraseasonal oscillations as key driver and source of predictability for the 2022 Pakistan record-breaking rainfall event","authors":"Jinhui Xie, Pang-Chi Hsu, June-Yi Lee, Lu Wang, Andrew G. Turner","doi":"10.1038/s41612-024-00809-9","DOIUrl":"10.1038/s41612-024-00809-9","url":null,"abstract":"In August 2022, Pakistan experienced unprecedented monsoon rains, leading to devastating floods and landslides affecting millions. While previous research has mainly focused on the contributions of seasonal and synoptic anomalies, this study elucidates the dominant influences of tropical and extratropical intraseasonal oscillations on both the occurrence and subseasonal prediction of this extreme rainfall event. Our scale-decomposed moisture budget analysis revealed that intense rainfall in Pakistan was triggered and sustained by enhanced vertical moisture transport anomalies, primarily driven by interactions between intraseasonal circulation anomalies and the prevailing background moisture field when tropical and mid-latitude systems coincided over Pakistan. Evaluation of subseasonal-to-seasonal prediction models further highlighted the critical role of tropical intraseasonal modes in causing this extreme rainfall event in Pakistan. Models that accurately predicted northward-propagating intraseasonal convection with a forecast lead time of 8–22 days demonstrated good skill in predicting the extreme event over Pakistan.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00809-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142487283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1038/s41612-024-00802-2
Qinxue Gu, Liping Zhang, Liwei Jia, Thomas L. Delworth, Xiaosong Yang, Fanrong Zeng, William F. Cooke, Shouwei Li
Coastal communities face substantial risks from long-term sea level rise and decadal sea level variations, with the North Atlantic and U.S. East Coast being particularly vulnerable under changing climates. Employing a self-organizing map-based framework, we assess the North Atlantic sea level variability and predictability using 5000-year sea level anomalies (SLA) from two preindustrial control model simulations. Preferred transitions among patterns of variability are identified, revealing long-term predictability on decadal timescales related to shifts in Atlantic meridional overturning circulation phases. Combining this framework with model-analog techniques, we demonstrate prediction skill of large-scale SLA patterns and low-frequency coastal SLA variations comparable to that from initialized hindcasts. Moreover, additional short-term predictability is identified after the exclusion of low-frequency signals, which arises from slow gyre circulation adjustment triggered by the North Atlantic Oscillation-like stochastic variability. This study highlights the potential of machine learning to assess sources of predictability and to enable long-term climate prediction.
{"title":"Exploring multiyear-to-decadal North Atlantic sea level predictability and prediction using machine learning","authors":"Qinxue Gu, Liping Zhang, Liwei Jia, Thomas L. Delworth, Xiaosong Yang, Fanrong Zeng, William F. Cooke, Shouwei Li","doi":"10.1038/s41612-024-00802-2","DOIUrl":"10.1038/s41612-024-00802-2","url":null,"abstract":"Coastal communities face substantial risks from long-term sea level rise and decadal sea level variations, with the North Atlantic and U.S. East Coast being particularly vulnerable under changing climates. Employing a self-organizing map-based framework, we assess the North Atlantic sea level variability and predictability using 5000-year sea level anomalies (SLA) from two preindustrial control model simulations. Preferred transitions among patterns of variability are identified, revealing long-term predictability on decadal timescales related to shifts in Atlantic meridional overturning circulation phases. Combining this framework with model-analog techniques, we demonstrate prediction skill of large-scale SLA patterns and low-frequency coastal SLA variations comparable to that from initialized hindcasts. Moreover, additional short-term predictability is identified after the exclusion of low-frequency signals, which arises from slow gyre circulation adjustment triggered by the North Atlantic Oscillation-like stochastic variability. This study highlights the potential of machine learning to assess sources of predictability and to enable long-term climate prediction.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-15"},"PeriodicalIF":8.5,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00802-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-21DOI: 10.1038/s41612-024-00803-1
Oliver T. Millin, Jason C. Furtado, Christopher Malloy
Extreme wintertime cold in the central United States (US) can drive excessive electricity demand and grid failures, with substantial socioeconomic effects. Predicting cold-induced demand surges is relatively understudied, especially on the subseasonal-to-seasonal (S2S) timescale of 2 weeks to 2 months. North American winter weather regimes are atmospheric tools that are based on persistent atmospheric circulation patterns, and have been linked to potential S2S predictability of extreme cold in the central US. We study the relationship between winter weather regimes and daily peak load across 13 balancing authorities in the Southwest Power Pool. Anomalous ridging across Alaska, the West Coast, and Greenland drive increases in demand and extreme demand risk. Conversely, anomalous troughing across the Arctic and North Pacific reduces extreme demand risk. Thus, weather regimes may not only be an important long-lead predictor for North American electricity load, but potentially a useful tool for end users and stakeholders.
{"title":"The impact of North American winter weather regimes on electricity load in the central United States","authors":"Oliver T. Millin, Jason C. Furtado, Christopher Malloy","doi":"10.1038/s41612-024-00803-1","DOIUrl":"10.1038/s41612-024-00803-1","url":null,"abstract":"Extreme wintertime cold in the central United States (US) can drive excessive electricity demand and grid failures, with substantial socioeconomic effects. Predicting cold-induced demand surges is relatively understudied, especially on the subseasonal-to-seasonal (S2S) timescale of 2 weeks to 2 months. North American winter weather regimes are atmospheric tools that are based on persistent atmospheric circulation patterns, and have been linked to potential S2S predictability of extreme cold in the central US. We study the relationship between winter weather regimes and daily peak load across 13 balancing authorities in the Southwest Power Pool. Anomalous ridging across Alaska, the West Coast, and Greenland drive increases in demand and extreme demand risk. Conversely, anomalous troughing across the Arctic and North Pacific reduces extreme demand risk. Thus, weather regimes may not only be an important long-lead predictor for North American electricity load, but potentially a useful tool for end users and stakeholders.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-8"},"PeriodicalIF":8.5,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00803-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-21DOI: 10.1038/s41612-024-00806-y
Chao Liu, Soon-Il An, Soong-Ki Kim, Malte F. Stuecker, Wenjun Zhang, Fei-Fei Jin, Jae-Heung Park, Leishan Jiang, Aoyun Xue, Xin Geng, Hyo-Jin Park, Young-Min Yang, Jong-Seong Kug
Pantropical climate interactions across ocean basins operate on a wide range of timescales and can improve the accuracy of climate predictions. Here, we show in observations that Central Pacific (CP) El Niño-like sea surface temperature (SST) anomalies have coevolved with tropical South Atlantic SST anomalies on a quasi-decadal (~10-year) timescale over the past seven decades. During the austral autumn–winter season, decadal warm SSTs in the tropical CP effectively induce tropical SST cooling in the South Atlantic, mainly by strengthening the South Atlantic subtropical anticyclone via an extratropical atmospheric wave teleconnection in the southern hemisphere. Partially coupled pacemaker simulations corroborate the observational findings, indicating that tropical CP decadal SSTs play a primary pacing role, while Atlantic feedback is of secondary importance throughout the study period. Our results suggest that the tropical CP could be an important source of decadal predictability for tropical South Atlantic SST and the surrounding climate.
{"title":"Synchronous decadal climate variability in the tropical Central Pacific and tropical South Atlantic","authors":"Chao Liu, Soon-Il An, Soong-Ki Kim, Malte F. Stuecker, Wenjun Zhang, Fei-Fei Jin, Jae-Heung Park, Leishan Jiang, Aoyun Xue, Xin Geng, Hyo-Jin Park, Young-Min Yang, Jong-Seong Kug","doi":"10.1038/s41612-024-00806-y","DOIUrl":"10.1038/s41612-024-00806-y","url":null,"abstract":"Pantropical climate interactions across ocean basins operate on a wide range of timescales and can improve the accuracy of climate predictions. Here, we show in observations that Central Pacific (CP) El Niño-like sea surface temperature (SST) anomalies have coevolved with tropical South Atlantic SST anomalies on a quasi-decadal (~10-year) timescale over the past seven decades. During the austral autumn–winter season, decadal warm SSTs in the tropical CP effectively induce tropical SST cooling in the South Atlantic, mainly by strengthening the South Atlantic subtropical anticyclone via an extratropical atmospheric wave teleconnection in the southern hemisphere. Partially coupled pacemaker simulations corroborate the observational findings, indicating that tropical CP decadal SSTs play a primary pacing role, while Atlantic feedback is of secondary importance throughout the study period. Our results suggest that the tropical CP could be an important source of decadal predictability for tropical South Atlantic SST and the surrounding climate.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-14"},"PeriodicalIF":8.5,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00806-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1038/s41612-024-00801-3
Joonsuk M. Kang, Tiffany A. Shaw, Sarah M. Kang, Isla R. Simpson, Yue Yu
Southern Hemisphere (SH) storminess has increased in the satellite era and recent work suggests comprehensive climate models significantly underestimate the trend. Here, we revisit this reanalysis-model trend discrepancy to better understand the mechanisms underlie it. A comprehensive like-for-like analysis shows reanalysis trends exhibit large uncertainty, and coupled climate model simulations exhibit weaker trends than most but not all reanalyses. However, simulations with prescribed sea surface temperature (SST) exhibit significantly greater storminess trends, particularly in the South Pacific, implying SST trend discrepancies in coupled simulations impact storminess trends. Using pacemaker simulations that correct Southern Ocean and tropical east Pacific SST trend discrepancies, we show that storminess trends in coupled simulations are underestimated because they do not capture the enhanced storminess resulting from Southern Ocean cooling and La-Nina-like teleconnection trends. Our findings emphasize large reanalysis uncertainty in SH circulation trends and the impact of regional SST trend discrepancies on circulation trends.
在卫星时代，南半球（SH）风暴增加，而最近的研究表明，综合气候模式大大低估了这一趋势。在此，我们重新审视了再分析与模式的趋势差异，以更好地理解其背后的机制。全面的同类分析表明，再分析的趋势具有很大的不确定性，耦合气候模式模拟的趋势弱于大多数再分析，但不是所有再分析。然而，具有规定海表温度（SST）的模拟显示出明显更大的风暴潮趋势，尤其是在南太平洋，这意味着耦合模拟中的 SST 趋势差异会影响风暴潮趋势。利用修正了南大洋和东太平洋热带海面温度趋势差异的起搏器模拟，我们发现耦合模拟中的暴雨趋势被低估了，因为它们没有捕捉到南大洋降温和类似拉尼娜的远距离联系趋势所导致的暴雨增强。我们的研究结果强调了再分析在 SH 环流趋势中的巨大不确定性，以及区域 SST 趋势差异对环流趋势的影响。
{"title":"Revisiting the reanalysis-model discrepancy in Southern Hemisphere winter storm track trends","authors":"Joonsuk M. Kang, Tiffany A. Shaw, Sarah M. Kang, Isla R. Simpson, Yue Yu","doi":"10.1038/s41612-024-00801-3","DOIUrl":"10.1038/s41612-024-00801-3","url":null,"abstract":"Southern Hemisphere (SH) storminess has increased in the satellite era and recent work suggests comprehensive climate models significantly underestimate the trend. Here, we revisit this reanalysis-model trend discrepancy to better understand the mechanisms underlie it. A comprehensive like-for-like analysis shows reanalysis trends exhibit large uncertainty, and coupled climate model simulations exhibit weaker trends than most but not all reanalyses. However, simulations with prescribed sea surface temperature (SST) exhibit significantly greater storminess trends, particularly in the South Pacific, implying SST trend discrepancies in coupled simulations impact storminess trends. Using pacemaker simulations that correct Southern Ocean and tropical east Pacific SST trend discrepancies, we show that storminess trends in coupled simulations are underestimated because they do not capture the enhanced storminess resulting from Southern Ocean cooling and La-Nina-like teleconnection trends. Our findings emphasize large reanalysis uncertainty in SH circulation trends and the impact of regional SST trend discrepancies on circulation trends.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-10"},"PeriodicalIF":8.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00801-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1038/s41612-024-00810-2
Xinyu Li, Riyu Lu, Guixing Chen, Ruidan Chen
It is generally believed that the Maritime Continent (MC) is rarely affected by tropical cyclones (TCs) due to its equatorial location. However, this study reveals that TCs in the tropical western North Pacific can significantly suppress rainfall over the MC and its surrounding seas, based on the composite analysis. This suppression effect of TCs exists across all phases of the Madden–Julian Oscillation (MJO). TCs greatly alleviate rainfall enhancement during the convective phases of the MJO and aggravate rainfall suppression during the suppressive phases. Particularly, TCs reduce the likelihood of extremely high rainfall in convective MJO phases from 9% to 5% and increase the likelihood of extremely low rainfall in suppressive MJO phases from 10% to 16%. The rainfall suppression is attributed to the lower-tropospheric southwesterly anomalies to the south of TCs, which result in moisture divergence over the MC. Additionally, the upper-tropospheric equatorward outflows of TCs also promote subsidence and suppress rainfall. This study introduces a new factor influencing the rainfall over the MC from a synoptic climatology perspective.
{"title":"Western North Pacific tropical cyclones suppress Maritime Continent rainfall","authors":"Xinyu Li, Riyu Lu, Guixing Chen, Ruidan Chen","doi":"10.1038/s41612-024-00810-2","DOIUrl":"10.1038/s41612-024-00810-2","url":null,"abstract":"It is generally believed that the Maritime Continent (MC) is rarely affected by tropical cyclones (TCs) due to its equatorial location. However, this study reveals that TCs in the tropical western North Pacific can significantly suppress rainfall over the MC and its surrounding seas, based on the composite analysis. This suppression effect of TCs exists across all phases of the Madden–Julian Oscillation (MJO). TCs greatly alleviate rainfall enhancement during the convective phases of the MJO and aggravate rainfall suppression during the suppressive phases. Particularly, TCs reduce the likelihood of extremely high rainfall in convective MJO phases from 9% to 5% and increase the likelihood of extremely low rainfall in suppressive MJO phases from 10% to 16%. The rainfall suppression is attributed to the lower-tropospheric southwesterly anomalies to the south of TCs, which result in moisture divergence over the MC. Additionally, the upper-tropospheric equatorward outflows of TCs also promote subsidence and suppress rainfall. This study introduces a new factor influencing the rainfall over the MC from a synoptic climatology perspective.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-8"},"PeriodicalIF":8.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00810-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1038/s41612-024-00788-x
Laura Jensen, Helena Gerdener, Annette Eicker, Jürgen Kusche, Stephanie Fiedler
We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.
{"title":"Observations indicate regionally misleading wetting and drying trends in CMIP6","authors":"Laura Jensen, Helena Gerdener, Annette Eicker, Jürgen Kusche, Stephanie Fiedler","doi":"10.1038/s41612-024-00788-x","DOIUrl":"10.1038/s41612-024-00788-x","url":null,"abstract":"We evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against a new global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. To account for different timescales in our analysis, we select regions in which the influence of interannual variability is relatively small and observed trends are assumed to be representative of the development over longer periods. Our results reveal distinct biases in drying and wetting trends in CMIP6 models for several world regions. Specifically, we see high model consensus for drying in the Amazon, which disagrees with the observed wetting. Other regions show a high consensus of models and observations suggesting qualitatively correctly simulated trends, e.g., for the Mediterranean and parts of Central Africa. A high model agreement might therefore falsely indicate a robust trend in water storage if it is not assessed in light of the observed developments. This underlines the potential use of maintaining an adequate observational capacity of water storage for climate change assessments.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-12"},"PeriodicalIF":8.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00788-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hydrological connectivity is crucial for understanding water-ecosystem dynamics, as it serves as a key link between different landscape units. However, the variability of hydrological connectivity in Central Asia remains unexplored, which poses challenges to a comprehensive understanding of ecohydrological processes. This study investigates the spatiotemporal patterns and driving mechanisms of hydrological connectivity in the Tarim River Basin (TRB), Central Asia, from 1990 to 2020, employing a novel approach that integrates remote sensing and reanalysis data. The results indicate an increasing trend in the hydrological connectivity index (HCI), with approximately 60% of the TRB exhibiting significant increases. Climate change exerts the greatest direct (0.59) and total (0.64) effects on HCI, with potential evapotranspiration (19.2%) and temperature (12.6%) being the dominant factors. In mountainous regions, climate change (0.65) is the primary driver, while human activities have a greater impact in the plains (−0.27). These findings offer a new framework for studying ecohydrological processes in arid regions.
{"title":"Climate warming positively affects hydrological connectivity of typical inland river in arid Central Asia","authors":"Chuanxiu Liu, Yaning Chen, Wenjing Huang, Gonghuan Fang, Zhi Li, Chenggang Zhu, Yongchang Liu","doi":"10.1038/s41612-024-00800-4","DOIUrl":"10.1038/s41612-024-00800-4","url":null,"abstract":"Hydrological connectivity is crucial for understanding water-ecosystem dynamics, as it serves as a key link between different landscape units. However, the variability of hydrological connectivity in Central Asia remains unexplored, which poses challenges to a comprehensive understanding of ecohydrological processes. This study investigates the spatiotemporal patterns and driving mechanisms of hydrological connectivity in the Tarim River Basin (TRB), Central Asia, from 1990 to 2020, employing a novel approach that integrates remote sensing and reanalysis data. The results indicate an increasing trend in the hydrological connectivity index (HCI), with approximately 60% of the TRB exhibiting significant increases. Climate change exerts the greatest direct (0.59) and total (0.64) effects on HCI, with potential evapotranspiration (19.2%) and temperature (12.6%) being the dominant factors. In mountainous regions, climate change (0.65) is the primary driver, while human activities have a greater impact in the plains (−0.27). These findings offer a new framework for studying ecohydrological processes in arid regions.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-12"},"PeriodicalIF":8.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00800-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1038/s41612-024-00799-8
Na-Yeon Shin, Daehyun Kang, Daehyun Kim, June-Yi Lee, Jong-Seong Kug
The summer MJO exhibits different characteristics from its winter counterpart, particularly distinguished by propagation in both eastward and northward directions, which is relatively less understood. Here, we explore the primary sources of the summer MJO predictability using Machine Learning (ML) based on the long-term climate model simulation and its transfer learning with the observational data. Our ML-based summer MJO prediction model shows a correlation skill of 0.5 at about 24-day forecast lead time. By utilizing eXplainable Artificial Intelligence (XAI), we discern Precipitable Water (PW) and Surface Temperature (TS) as the most influential sources for the summer MJO predictability. We especially identify the roles of PW and TS in the eastern and northern Indian Ocean (EIO and NIO) regions on the propagation characteristics of the summer MJO through XAI-based sensitivity experiments. These results suggest that ML-based approaches are useful for identifying sources of predictability and their roles in climate phenomena.
{"title":"Data-driven investigation on the boreal summer MJO predictability","authors":"Na-Yeon Shin, Daehyun Kang, Daehyun Kim, June-Yi Lee, Jong-Seong Kug","doi":"10.1038/s41612-024-00799-8","DOIUrl":"10.1038/s41612-024-00799-8","url":null,"abstract":"The summer MJO exhibits different characteristics from its winter counterpart, particularly distinguished by propagation in both eastward and northward directions, which is relatively less understood. Here, we explore the primary sources of the summer MJO predictability using Machine Learning (ML) based on the long-term climate model simulation and its transfer learning with the observational data. Our ML-based summer MJO prediction model shows a correlation skill of 0.5 at about 24-day forecast lead time. By utilizing eXplainable Artificial Intelligence (XAI), we discern Precipitable Water (PW) and Surface Temperature (TS) as the most influential sources for the summer MJO predictability. We especially identify the roles of PW and TS in the eastern and northern Indian Ocean (EIO and NIO) regions on the propagation characteristics of the summer MJO through XAI-based sensitivity experiments. These results suggest that ML-based approaches are useful for identifying sources of predictability and their roles in climate phenomena.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00799-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1038/s41612-024-00787-y
Libin Ma, Mingting Li, Fei Liu, Juan Li
Understanding the impacts of the Indonesian Throughflow (ITF) on the eastward propagation of the Madden-Julian Oscillation (MJO) is crucial for accurately simulating the MJO and achieving high-skill sub-seasonal predictions. Our analyses demonstrate a significant enhancement of MJO eastward propagation due to the strong ITF. Blocking the ITF decreases the eastward sea surface temperature (SST) gradient over the tropical Indian Ocean, hindering MJO propagation across the Maritime Continent (MC). Removing the MJO circulation-induced intraseasonal variability of the ITF transport also weakens the eastward propagation of the MJO, as the MJO easterly winds enhance the ITF transport and warm the eastern tropical Indian Ocean. These experiments reveal that mean and intraseasonal variability of the ITF transport contribute to 73% and 42% of the eastward propagation of the MJO over the MC, respectively. The findings presented in this study highlight the significant role of the ITF in shaping the propagation of the MJO.
{"title":"Indonesian Throughflow promoted eastward propagation of the Madden-Julian Oscillation","authors":"Libin Ma, Mingting Li, Fei Liu, Juan Li","doi":"10.1038/s41612-024-00787-y","DOIUrl":"10.1038/s41612-024-00787-y","url":null,"abstract":"Understanding the impacts of the Indonesian Throughflow (ITF) on the eastward propagation of the Madden-Julian Oscillation (MJO) is crucial for accurately simulating the MJO and achieving high-skill sub-seasonal predictions. Our analyses demonstrate a significant enhancement of MJO eastward propagation due to the strong ITF. Blocking the ITF decreases the eastward sea surface temperature (SST) gradient over the tropical Indian Ocean, hindering MJO propagation across the Maritime Continent (MC). Removing the MJO circulation-induced intraseasonal variability of the ITF transport also weakens the eastward propagation of the MJO, as the MJO easterly winds enhance the ITF transport and warm the eastern tropical Indian Ocean. These experiments reveal that mean and intraseasonal variability of the ITF transport contribute to 73% and 42% of the eastward propagation of the MJO over the MC, respectively. The findings presented in this study highlight the significant role of the ITF in shaping the propagation of the MJO.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-8"},"PeriodicalIF":8.5,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00787-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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