Khaiwal Ravindra, Sahil Kumar, Abhishek Kumar, Suman Mor
{"title":"Enhancing accuracy of air quality sensors with machine learning to augment large-scale monitoring networks","authors":"Khaiwal Ravindra, Sahil Kumar, Abhishek Kumar, Suman Mor","doi":"10.1038/s41612-024-00833-9","DOIUrl":"10.1038/s41612-024-00833-9","url":null,"abstract":"Low-cost sensors have revolutionized air quality monitoring, however, precision is questioned compared to reference instruments. Hence, the performance of two widely used PM2.5 Sensors, Purple Air (PA) and ATMOS, were evaluated over a 10-month period in the North Western-Indo Gangetic Plains (NW-IGP). In-field collocation with Beta Attenuation Monitor found low R2 values; 0.40 for ATMOS and 0.43 for PA. To calibrate and improve the accuracy of sensors, five Machine Learning (ML) models and an empirical relative humidity correction methodology were used separately for both sensors. Out of these, the Decision Tree outperformed others, and R2 values improved to 0.996 for ATMOS and 0.999 for PA. Root mean square error reduced from 34.6 µg/m3 to 0.731 µg/m3 for ATMOS and from 77.7 µg/m3 to 0.61 µg/m3 for PA, while using DT as a calibrating model. The study reveals the best-performing ML model for correcting PM2.5 sensor data, enhancing the accuracy of air quality monitoring systems.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00833-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142888658","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}
{"title":"Sub-daily scale rainfall extremes in India and incongruity between hourly rain gauges data and CMIP6 models","authors":"Kadiri Saikranthi, Basivi Radhakrishna, Madhavan Nair Rajeevan","doi":"10.1038/s41612-024-00885-x","DOIUrl":"10.1038/s41612-024-00885-x","url":null,"abstract":"Self-recording rain gauges hourly rainfall data from 1969 to 2010 have been utilized to identify rain events at a sub-daily scale. At the sub-daily scale, a significant decrease in the frequency of heavy rainfall events (HREs) is observed over central India and northeast India, while an increase is observed over the northern west coast of India. Frequency of short-duration HREs over central India and long duration HREs over northern west coast of India is increased in the recent decades than in earlier decades. Incongruity with the observations, CMIP6 historical and AMIP high temporal resolution models are not able to simulate the short-duration HREs and, in turn, the observed trends at a sub-daily scale over the India landmass. The inability of CMIP6 models to predict short-duration HREs suggests caution in predicting future projections of extreme precipitation at a sub-daily scale and highlights the need for further improvements in climate models.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00885-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142888600","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}
{"title":"Novel perspectives on multiple-peak diurnal convection over a tropical mountainous island from idealized large-eddy simulations","authors":"Yu-Hsiu Wang, Wei-Ting Chen, Chien-Ming Wu","doi":"10.1038/s41612-024-00884-y","DOIUrl":"10.1038/s41612-024-00884-y","url":null,"abstract":"Two robust peaks in the diurnal evolution of orographically-locked precipitation are simulated in large-eddy simulations with an idealized ocean-plain-mountain topography. The ensemble experiment design is guided by sounding statistics from summertime afternoon thunderstorms in Taiwan to obtain realistic variability of free-tropospheric moisture associated with the intensity of the summertime subtropical high. The convection in the first peak is directly modulated by convective available potential energy, while the convection in the second peak is associated with low-level moist static energy (MSE) transport by the island-scale (40-km) local circulation, producing more extreme rainfall. When the initial free troposphere is drier, the convection in the second peak is strengthened. Both the environmental adjustments by the first peak and local circulation development contribute to the sensitivity of the second peak to free-tropospheric moisture. This work highlights the critical roles of convection-environment interaction and upstream MSE supply in enhancing extreme diurnal precipitation over complex topography.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-14"},"PeriodicalIF":8.5,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00884-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142888659","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}
{"title":"Mechanism underlying the correlation between the warming-wetting of the Qinghai-Tibet Plateau and atmospheric energy changes in high-impact oceanic areas","authors":"Na Dong, Xiangde Xu, Renhe Zhang, Chan Sun, Wenyue Cai, Runze Zhao","doi":"10.1038/s41612-024-00849-1","DOIUrl":"10.1038/s41612-024-00849-1","url":null,"abstract":"The powerful thermal driving force of the Qinghai-Tibet Plateau (QTP) exerts a significant influence on weather, climate, and environmental processes in Asia and across the globe. This paper investigates the causes of climate change on the QTP from the perspective of global atmospheric energy transport and water cycle. During summer, a “hollow energy pool” has been discovered in the troposphere, with its energy center located above the QTP, the “Asian water tower”. Our study indicates that the QTP serves as a critical “window” for the global transport of water vapor and energy. Since 1991, the total atmospheric energy (TAE) and precipitation in the warming-wetting region of the QTP (central and northern plateau) have exhibited interdecadal growth. Furthermore, the TAE of the plateau is closely linked to the TAE and water vapor of oceans at mid-low latitudes, and even in the southern hemisphere, the increased precipitation in the warming-wetting region of the plateau has been mainly regulated by the atmospheric energy and water vapor transport structures over the equatorial western Pacific, southwestern Pacific, and southern Indian Ocean, we further reveal the energy transport channel from the warming oceanic areas of the southern and northern hemispheres to the QTP. This study deepens the novel understanding of atmospheric energy accompanying water vapor transport in the southern and northern hemispheres, which is of significant importance for understanding the responses of energy and water cycle in the warming-wetting of the QTP and global climate change.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00849-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142886853","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}
Xinhui Li, Jiayu Zheng, Chunzai Wang, Xiayan Lin, Zhixiong Yao
{"title":"Unraveling the roles of jet streams on the unprecedented hot July in Western Europe in 2022","authors":"Xinhui Li, Jiayu Zheng, Chunzai Wang, Xiayan Lin, Zhixiong Yao","doi":"10.1038/s41612-024-00880-2","DOIUrl":"10.1038/s41612-024-00880-2","url":null,"abstract":"Western Europe experienced an unprecedentedly hot July in 2022, which significantly impacted ecosystems and society. Our observational and numerical modeling study reveals that this event was influenced by anomalous North Atlantic and Eurasian jet streams. The northeastward shift of the North Atlantic jet stream, driven by sea surface temperature gradients, and the curving of the Eurasian jet stream, affected by rainfall anomalies in Pakistan, enhanced atmospheric subsidence over western Europe. This research highlights the crucial role of the synergistic behavior of the North Atlantic and Eurasian jet streams in driving extreme heat over Western Europe. Furthermore, CMIP6 climate model projections suggest that under the SSP585 scenario, similar jet stream configurations could lead to even more intense extreme temperatures (~7.02 ± 0.61 °C) compared to the current climatological mean.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00880-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884647","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}
{"title":"Seasonal phase change of the North Atlantic Tripole Sea surface temperature predicted by air-sea coupling","authors":"Haipeng Yu, Shanling Cheng, Jianping Huang, Zeyong Hu, Haojie Wu, Xin Wang","doi":"10.1038/s41612-024-00882-0","DOIUrl":"10.1038/s41612-024-00882-0","url":null,"abstract":"The North Atlantic Tripole sea surface temperature anomaly (NAT SSTA) is critical for predicting climate in Eurasia. Predictions for summer climate anomalies currently assume the NAT SSTA phase persists from boreal winter through summer. When NAT phase switches, predictions become unreliable. However, the NAT phase sustained/reversal mechanism from boreal winter to spring remains unclear. This study demonstrates that the evolution of the NAT phase could be driven by the North Atlantic Oscillation (NAO). When NAO phase persists (switches) during preceding boreal winter, the NAO-driven wind anomalies favor maintenance (transition) of NAT phase by causing sea surface heat flux anomalies. Meanwhile, NAT SSTA causes eddy-mean flow interaction by increasing atmospheric baroclinity, thereby generating positive feedback on the former NAO phase. The NAO phase change is leading 1–3 months for the NAT phase. These findings deepen our understanding of the interaction between NAO and NAT and provide implications for seasonal prediction in Eurasia.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-13"},"PeriodicalIF":8.5,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00882-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879662","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}
{"title":"Advancing symbolic regression for earth science with a focus on evapotranspiration modeling","authors":"Qingliang Li, Cheng Zhang, Zhongwang Wei, Xiaochun Jin, Wei Shangguan, Hua Yuan, Jinlong Zhu, Lu Li, Pingping Liu, Xiao Chen, Yuguang Yan, Yongjiu Dai","doi":"10.1038/s41612-024-00861-5","DOIUrl":"10.1038/s41612-024-00861-5","url":null,"abstract":"Artificial Intelligence (AI) assumes a pivotal role in Earth science, leveraging deep learning’s predictive capabilities. Despite its prevalence, the impact of AI on scientific discovery remains uncertain. In Earth sciences, the emphasis extends beyond mere accuracy, striving for groundbreaking discoveries with distinct physical properties essential for driving advancements through thorough analysis. Here, we introduce a novel knowledge-guided deep symbolic regression model (KG-DSR) incorporating prior knowledge of physical process interactions into the network. Using KG-DSR, we successfully derived the Penman-Monteith (PM) equation and generated a novel surface resistance parameterization. This new parameterization, grounded in fundamental cognitive principles, surpasses the conventional theory currently accepted in surface resistance parameterization. Importantly, the explicit physical processes generated by AI can generalize to future climate scenarios beyond the training data. Our results emphasize the role of AI in unraveling process intricacies and ushering in a new paradigm in tasks related to “AI for Land Surface Modeling.”","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-16"},"PeriodicalIF":8.5,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00861-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142879626","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}
Gordon B. Bonan, Clara Deser, William R. Wieder, Danica L. Lombardozzi, Flavio Lehner
{"title":"When is a trend meaningful? Insights to carbon cycle variability from an initial-condition large ensemble","authors":"Gordon B. Bonan, Clara Deser, William R. Wieder, Danica L. Lombardozzi, Flavio Lehner","doi":"10.1038/s41612-024-00878-w","DOIUrl":"10.1038/s41612-024-00878-w","url":null,"abstract":"Internal climate variability (ICV) creates a range of climate trajectories, which are superimposed upon the forced response. A single climate model realization may not represent forced change alone and may diverge from other realizations, as well as observations, due to ICV. We use an initial-condition large ensemble of simulations with the Community Earth System Model (CESM2) to show that ICV produces a range of outcomes in the terrestrial carbon cycle. Trends in gross primary production (GPP) from 1991 to 2020 differ among ensemble members due to the different climate trajectories resulting from ICV. We quantify how ICV imparts on GPP trends and apply our methodology to the observational record. Observed changes in GPP at two long-running eddy covariance flux towers are consistent with ICV, challenging the understanding of forced changes in the carbon cycle at these locations. A probabilistic framework that accounts for ICV is needed to interpret carbon cycle trends.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00878-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862420","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}
{"title":"Robust increase in South Asian monsoon rainfall under warming driven by extratropical clouds and ocean","authors":"Yong-Jhih Chen, Yen-Ting Hwang, Jian Lu","doi":"10.1038/s41612-024-00843-7","DOIUrl":"10.1038/s41612-024-00843-7","url":null,"abstract":"The responses of South Asian Monsoon (SAM) circulation under global warming are known to be highly uncertain, leading to the widespread of SAM rainfall projections among models. Here, we show that the uncertain SAM circulation in Coupled Model Intercomparison Project Phase 6 models consists of two robust components that partly offset each other: a weakening component linked to a global thermodynamic constraint and a northward shift component understood through a regional 2D energetic perspective. We further attribute the robust northward shift of SAM circulation to positive cloud feedback over the Eurasia Continent and heat uptake in the Southern Ocean. A set of climate model simulations supports the finding that SAM rainfall increase is primarily due to the northward shift of circulation driven by extratropical processes. This energetic perspective opens new avenues for predicting monsoon rainfall by connecting circulation changes to radiative forcing, feedbacks, and ocean heat uptake.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-10"},"PeriodicalIF":8.5,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00843-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862448","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}
Mengyan Chen, Matthew Collins, Jin-Yi Yu, Xin Wang, Lei Zhang, Chi-Yung Tam
{"title":"Emerging influence of the Australian Monsoon on Indian Ocean interannual variability in a warming climate","authors":"Mengyan Chen, Matthew Collins, Jin-Yi Yu, Xin Wang, Lei Zhang, Chi-Yung Tam","doi":"10.1038/s41612-024-00879-9","DOIUrl":"10.1038/s41612-024-00879-9","url":null,"abstract":"The Indian Ocean Dipole (IOD) and Tripole (IOT) represent primary modes of interannual variability in the Indian Ocean, impacting both regional and global climate. Unlike the IOD, which is closely related to the El Niño-Southern Oscillation (ENSO), our findings unveil a substantial influence of the Australian Monsoon on the IOT. An anomalously strong Monsoon induces local sea surface temperature (SST) variations via the wind-evaporation-SST mechanism, triggering atmospheric circulation anomalies in the eastern Indian Ocean. These circulation changes lead to changes in oceanic heat transport, facilitating the formation of the IOT. Our analysis reveals a strengthening connection between the Australian Monsoon and the IOT in recent decades, with a projected further strengthening under global warming. This contrasts with the diminished coupling between ENSO and IOD in recent decades from observations and model projections, illustrating evolving Indian Ocean dynamics under the warming climate.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-8"},"PeriodicalIF":8.5,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00879-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862476","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}