Journal of Atmospheric and Solar-Terrestrial Physics最新文献

{"title":"Evaluating water use efficiency and CO₂ absorption in plants under rising atmospheric carbon dioxide levels","authors":"Alberto Boretti","doi":"10.1016/j.jastp.2024.106409","DOIUrl":"10.1016/j.jastp.2024.106409","url":null,"abstract":"<div><div>While elevated CO₂ levels have been shown to initially enhance photosynthesis, the long-term global effects on photosynthesis rates are influenced by a complex set of interacting factors. Although theoretical thresholds exist where further increases in CO₂ could potentially reduce photosynthesis, current research suggests that these levels remain far off. Contrary to recent reports suggesting a decline in water use efficiency (WUE) in plants, a review of the latest literature indicates that plants are, in fact, using water more efficiently while continuing to absorb atmospheric CO₂. This analysis highlights that rising CO₂ concentrations are contributing to improved WUE in plants, reflecting an adaptive response rather than a decline in functionality.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"266 ","pages":"Article 106409"},"PeriodicalIF":1.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One-hour-ahead solar irradiance forecast based on real-time K-means++ clustering on the input side and CNN-LSTM","authors":"Yunxiao Chen ,&nbsp;Chaojing Lin ,&nbsp;Jinfu Liu ,&nbsp;Daren Yu","doi":"10.1016/j.jastp.2024.106405","DOIUrl":"10.1016/j.jastp.2024.106405","url":null,"abstract":"<div><div>With the increasing proportion of photovoltaic power generation in the power system, accurate solar irradiance forecasting is crucial for power grid scheduling. The paper proposes a approach of clustering modeling and joint forecasting for solar irradiance: firstly, by using the real-time K-means++ to cluster the GHI sequence on the input side of the model, the model input is divided into 4 clusters. The number of clusters and clustering methods are quickly determined through sensitivity experiments. Then 4 CNN-LSTM models, corresponding to the 4 clusters, are separately established and trained to fully extract multivariate and multi-temporal information from the input side. These 4 models are combined to achieve 1-h-ahead solar irradiance forecast with higher accuracy. To verify the effectiveness of the proposed method, Auto regressive (AR), Convolutional neural network (CNN), Long short-term memory (LSTM) and Gradient boosting decision tree (GBDT) are used as comparative models. The results indicate that the proposed K-means++_CNN-LSTM is a feasible method, with MAE decreasing by about 9.13%, RMSE decreasing by about 6.58%, and <span><math><mrow><mi>ρ</mi></mrow></math></span> increasing by about 1.46%, compared to K-means++_AR. Finally, T-test is used to verify the positive impact of the proposed framework on model accuracy.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"266 ","pages":"Article 106405"},"PeriodicalIF":1.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143179766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multifractal detrended cross-correlation coefficient for cosmic ray and sunspot time series","authors":"D. Sierra-Porta","doi":"10.1016/j.jastp.2024.106407","DOIUrl":"10.1016/j.jastp.2024.106407","url":null,"abstract":"<div><div>This study delves into the multifractal cross-correlations between cosmic ray intensity and sunspot numbers, addressing the shortcomings of traditional correlation analyses that often fail to capture the intricate and multifractal nature of these time series. Cosmic rays and solar activity are critical components of space weather dynamics, and understanding their interactions is essential for predicting space weather events that can affect satellite operations, communication systems, and even climate on Earth. We employ Multifractal Detrended Cross-Correlation Analysis (MFDCCA) to explore these complex relationships across a range of time scales. Our methodology involves segmenting the time series into windows of varying lengths, from 50 to 3900 days, and calculating cross-correlation coefficients for different polynomial fitting orders and fluctuation orders <span><math><mrow><mi>q</mi><mo>=</mo><mrow><mo>[</mo><mn>0</mn><mo>.</mo><mn>5</mn><mo>,</mo><mn>1</mn><mo>,</mo><mn>2</mn><mo>,</mo><mn>3</mn><mo>,</mo><mn>4</mn><mo>,</mo><mn>5</mn><mo>]</mo></mrow></mrow></math></span>, using polynomial orders of 2, 3, 4, and 5. This approach allows us to capture the multifractal properties and temporal dependencies within and between the series.</div><div>Our analysis reveals significant multifractal correlations, with the highest correlation coefficient of 0.876 occurring for <span><math><mrow><mi>q</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>5</mn></mrow></math></span> and polynomial order 2 with a lag of 57 days. The results demonstrate that higher polynomial orders result in more stable and robust coefficients, indicating stronger correlations on larger scales. These findings highlight the efficacy of advanced techniques like MFDCCA in uncovering the complex interactions between cosmic rays and solar activity, which are often missed by conventional methods. The implications of our study extend to the enhancement of space weather prediction models. By incorporating additional heliophysical variables such as solar wind conditions, interplanetary magnetic field data, and indices of coronal mass ejections or solar flares, future research can construct more comprehensive models that better capture the multifractal interactions governing these phenomena. This expanded understanding is crucial for improving the accuracy of space weather forecasts and mitigating the potential impacts of space weather events on technological and natural systems.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"266 ","pages":"Article 106407"},"PeriodicalIF":1.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aerosol radiation characteristics based on Himawari-8 and AERONET in Beijing city","authors":"Qianjun Mao ,&nbsp;Xiaoyan Zhang","doi":"10.1016/j.jastp.2024.106411","DOIUrl":"10.1016/j.jastp.2024.106411","url":null,"abstract":"<div><div>Aerosol radiative forcing (ARF) is an important parameter that describes the impact of atmospheric aerosols on the earth-atmosphere radiation balance. This parameter holds significant importance for environmental monitoring and understanding climate change. Aerosol optical depth (AOD) reflects the degree of atmospheric pollution and plays a key role in evaluating ARF. In this paper, the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) is utilized to calculate the ARF in different AOD in Beijing. The variation characteristics of ARF at different time scales are also studied. Meanwhile, the characteristics of ARF under different cloud types are analyzed, and the coupling relationship between cloud parameters and ARF is proposed. The results show the ARF of absorptive aerosol is comparable to that of fine-mode aerosol, while coarse-mode aerosol have the minimum ARF. The ARF varies significantly under different cloud types. The ARF varies from −59.18 ± 11.64 W/m² to −104.52 ± 20.90 W/m² at the bottom of atmosphere (BOA), from −9.94 ± 1.99 W/m² to −27.41 ± 4.11 W/m² at the top of the atmosphere (TOA), and from 49.24 ± 9.85 W/m² to 77.11 ± 15.42 W/m² at the atmosphere (ATM). The results also show a strong correlation between cloud optical thickness and ARF among cloud parameters. This paper contributes to a deeper understanding of aerosol-cloud interactions in the earth-atmosphere system and is important for predicting future climate change.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"266 ","pages":"Article 106411"},"PeriodicalIF":1.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143179767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermodynamic control of lightning activity in premonsoon and monsoon season over the Indian region","authors":"B. Abida Choudhury,&nbsp;M.I.R. Tinmaker","doi":"10.1016/j.jastp.2024.106410","DOIUrl":"10.1016/j.jastp.2024.106410","url":null,"abstract":"<div><div>Understanding the relationship between lightning activity and atmospheric thermodynamics is important for improving thunderstorm forecasting and mitigating lightning-related hazards. The study investigates the linkage between lightning activity and thermodynamic indices over the Indian subcontinent during pre-monsoon and monsoon seasons across 17 years (1998–2014). The flash count data was obtained from the Tropical Rainfall Measuring Mission's (TRMM) Lightning Imaging Sensor (LIS); the upper air sounding data for thermodynamic indices was archived from the University of Wyoming. Additionally, air temperature and relative humidity data at various pressure levels were retrieved from the National Oceanic and Atmospheric Administration (NOAA) during the same period over the Indian region. In the present study, the results indicate that the flash counts, surface maximum temperature, and Deep Convective Index (DCI) show a high peak in the month of May, before the onset of monsoon season. The higher peak of surface maximum temperature and DCI value is associated with strong convection which plays a crucial role in the occurrence of high lightning activity. The Bowen ratio (BR), planetary boundary layer (PBL), and Vertical Total Index (VTI) show a high peak in May. These are because of increased sensible heat flux and a strong vertical lapse rate. The PBL and high Cross Total Index (CTI) values contribute to more lightning strikes during the pre-monsoon season. The decrease in flash count and thermodynamic indices after the onset of monsoon season is due to the transport of more moisture from the ocean into the free atmosphere, large cloud coverage, shallow convection, slow charging mechanism, low cloud electrification and hence low lightning activity. The present study underscores the importance of evaluating threshold values of thermodynamic indices during seasonal transitions (premonsoon to monsoon season), which is useful for predicting the severity of thunderstorm formation and lightning intensity over the Indian region.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"268 ","pages":"Article 106410"},"PeriodicalIF":1.8,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143270166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal variability of ozone and its precursors at tropical megacity, Bengaluru, India: Effect of volatile organic compounds and meteorology","authors":"G. Dhanya ,&nbsp;T.S. Pranesha ,&nbsp;Sandip Nivdange ,&nbsp;Kamsali Nagaraja ,&nbsp;B.S. Murthy ,&nbsp;D.M. Chate ,&nbsp;Gufran Beig ,&nbsp;Nitin R. Karmalkar","doi":"10.1016/j.jastp.2024.106388","DOIUrl":"10.1016/j.jastp.2024.106388","url":null,"abstract":"<div><div>Routine observations of surface ozone (O₃) and its precursors (NO, NO₂, NOx) were taken over Bengaluru, a southern megacity, India, for 4 years period between January 2015 and December 2018. The seasonal variations of O₃, NO, NO₂, and NOx have been analysed to understand the short-term variability of the pollutants at this site. The magnitude of O₃ varied significantly by season, with maximum concentration during winter (13.07 ppbv) and minimum concentration during monsoon (9.52 ppbv). The highest concentration was observed in the post-monsoon season (17.38 ppbv) for NO, while NO₂ and NO_x showed the highest (41.75, 50.42 ppbv) in the winter season. The lowest concentrations of NO (5.70 ppbv), NO₂ (30.43 ppbv) and NOx(36.28 ppbv) were observed in summer. An estimate was performed to determine the site's VOC-NOx sensitivity, using the TNMHC/NO_X ratio as a photochemical measure. This ratio indicates that the study region is NO_X responsive in all seasons. Analysis was done on the effects of meteorological factors such as temperature, water vapour, and ventilation coefficient on pollutants. Higher correlation of O₃ with temperature showed the role of photochemical reactions in the formation of ozone and water vapour content leads to the removal of ozone concentration. The influence of meteorological variables on NO₂ and TNMHC did not appear to be very significant. An analysis of CAMS data with real-time measurements of ozone and oxides of nitrogen showed that ozone is significantly correlated, while nitrogen oxides are not significantly correlated with CAMS data.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106388"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mean winds and tidal variability from troposphere to the thermosphere retrieved from combined ground based and space borne measurements","authors":"A. Kalyan Teja ,&nbsp;M. Venkat Ratnam ,&nbsp;S. Vijaya Bhaskara Rao","doi":"10.1016/j.jastp.2024.106389","DOIUrl":"10.1016/j.jastp.2024.106389","url":null,"abstract":"<div><div>An attempt has been made to obtain mean winds covering the complete middle and upper atmosphere over a tropical region, Tirupati(13.5°N, 79.2°E) using a combined dataset of ERA5 reanalysis, SVU-meteor radar, and ICON/MIGHTI after comprehensive validation. Regardless of the season, thermospheric(200–300 km) and mesospheric(80–100 km) winds exhibit significant diurnal variability. Mean winds exhibit two distinct semi-annual oscillations at the stratopause and in the mesosphere. Tidal amplitudes are larger in meridional winds compared to that of zonal winds in the MLT region. This work has the potential in the field of numerical modeling of atmospheric circulation, especially to verify numerical simulations.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106389"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative time series analysis of SARIMA, LSTM, and GRU models for global SF6 emission management system","authors":"Ganime Tuğba Önder","doi":"10.1016/j.jastp.2024.106393","DOIUrl":"10.1016/j.jastp.2024.106393","url":null,"abstract":"<div><div>To maintain the balance of the atmosphere, the amount of change in greenhouse gas emissions must be under control. In order to create a management system and take forward-looking steps in this regard, there is no concrete data other than prediction models today. The success of prediction methods is better understood by comparing multiple methods. This research estimates the changes in the emissions of Sulfur Hexafluoride gas (SF₆) in the atmosphere using Seasonal Autoregressive Integrated Moving Average Model (SARIMA), Long-Short Term Memory Neural Network (LSTM) and Gated Recurrent Unit (GRU) forecast models and compares their accuracies. Focusing on monthly SF₆ emission values Between 1998; 2023, time series analysis was performed to predict future emission figures. The actual values and forecast results were compared and evaluated with performance criteria such as R², RMSE, NSE, MAE and MAPE%. The findings of this research highlight a continuous upward trend in SF₆ emissions and project that emission levels could approximately double from current levels by 2050. During the analysis process, all three methods performed well in estimating global SF₆ gas emissions. The LSTM model generally outperformed SARIMA and GRU models, having the lowest MAPE (0.003%), MAE (0.0003), RMSE (0.0003), and R² (1) values. It also exhibited very high predictive success with an NSE value of 0.9991. Therefore, it was determined to be the most suitable estimation method with the least error. The aim of this study is to contribute scientifically to the reduction strategies of SF₆ emissions.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106393"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient three-source model for Schumann resonance","authors":"A.P. Nickolaenko","doi":"10.1016/j.jastp.2024.106395","DOIUrl":"10.1016/j.jastp.2024.106395","url":null,"abstract":"<div><div>An efficient and simple model of global thunderstorm activity is described, which allows computing the diurnal and seasonal variations of the peak frequency of the first Schumann resonance (SR) mode. The model results are compared with the long-term monitoring of the diurnal - seasonal variations of the first SR frequency recorded in the vertical electric field component. The records were performed at the Hungarian Széchenyi István Geophysical Observatory or the Nagycenk Geophysical observatory (NCK; 47.6°N, 16.7°E). They cover the 16-year period ranging from Jan. 1994 to Dec. 2009. Comparison of model data with experimental observations allowed formulating the following conclusions. The model of the global thunderstorm activity is rather simple, it suggests that position of the global thunderstorm centers in Asia, Africa, and America varies from month to month, but it recurs from year to year. The only exception in spatial parameters is the effective width of the area occupied by lightning strokes, which is found from the observational data. Diurnal variations in thunderstorm intensity correspond to classical WMO data. In spite of its simplicity, the model is quite efficient; it allows accurately compute the diurnal variations of the first mode peak frequency. Deviations of the model <em>f</em>₁ values from those observed experimentally do not exceed 1% while the cross-correlation coefficient of their temporal variations is equal to 0.5–0.6. Authors hope to apply this model in future studies, as well as in interpreting observations at other field sites. Extension of comparable data will clarify the effective parameters of the global thunderstorm activity serving as the source of SR oscillations.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106395"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling of Zenith Tropospheric Delay using ERA5 data over East African region","authors":"Geoffrey Andima ,&nbsp;Richard Cliffe Ssenyunzi ,&nbsp;Emirant Bertillas Amabayo ,&nbsp;Alessandra Mascitelli ,&nbsp;Eugenio Realini","doi":"10.1016/j.jastp.2024.106390","DOIUrl":"10.1016/j.jastp.2024.106390","url":null,"abstract":"<div><div>The Zenith Tropospheric Delay (ZTD) is a crucial parameter in meteorology and climate research, often estimated from surface meteorological parameters and Global Navigation Satellite Systems (GNSS) observations. In East Africa, the lack of reliable surface meteorological data and gaps in GNSS observations compromise the accuracy and reliability of ZTD data. To address this issue, site-specific ZTD models were developed using ERA5 data from 2013 to 2017, employing Empirical Orthogonal Function (EOF) analysis. The accuracy of the proposed EOF models was validated using the tropospheric product from the Nevada Geodetic Laboratory (NGL) as a reference and compared to the Global Pressure and Temperature 3 (GPT3) ZTD model. The results of the study show that the EOF ZTD models significantly outperformed the GPT3 model, reducing Mean bias (MnB) by 72.3% and Root Mean Square Error (RMSE) by 3.0%. EOF models performed particularly well for stations near the equator (latitudes 4°S and 4°N) and between latitudes 12° S and 4° S in terms of MnB and RMSE, respectively. Seasonally, EOF models surpassed the GPT3 model in MnB and RMSE across most seasons near the equator, except during the September–October–November (SON) period, where GPT3 showed an 85.5% better performance in MnB. For stations between latitudes 12° S and 4° S, GPT3 generally performed better in terms of RMSE, except during the March–April–May (MAM) period, where the EOF model excelled. However, the EOF model consistently showed better (reduced) MnB in this region. This study demonstrates that the EOF method is a viable alternative for estimating ZTD in areas with limited surface meteorological data and GNSS observation gaps. The site-specific ZTD models developed using the EOF method can significantly improve the accuracy and reliability of ZTD data, with broad applications in geodesy, atmospheric science, and navigation among others.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106390"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143153072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}