Pub Date : 2025-01-01DOI: 10.1016/j.jastp.2024.106411
Qianjun Mao , Xiaoyan Zhang
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.
{"title":"Aerosol radiation characteristics based on Himawari-8 and AERONET in Beijing city","authors":"Qianjun Mao , 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/m<sup>2</sup> to −104.52 ± 20.90 W/m<sup>2</sup> at the bottom of atmosphere (BOA), from −9.94 ± 1.99 W/m<sup>2</sup> to −27.41 ± 4.11 W/m<sup>2</sup> at the top of the atmosphere (TOA), and from 49.24 ± 9.85 W/m<sup>2</sup> to 77.11 ± 15.42 W/m<sup>2</sup> 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}
Pub Date : 2024-12-24DOI: 10.1016/j.jastp.2024.106410
B. Abida Choudhury, M.I.R. Tinmaker
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.
{"title":"Thermodynamic control of lightning activity in premonsoon and monsoon season over the Indian region","authors":"B. Abida Choudhury, 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}
Pub Date : 2024-12-01DOI: 10.1016/j.jastp.2024.106388
G. Dhanya , T.S. Pranesha , Sandip Nivdange , Kamsali Nagaraja , B.S. Murthy , D.M. Chate , Gufran Beig , Nitin R. Karmalkar
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 NOx 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/NOX ratio as a photochemical measure. This ratio indicates that the study region is NOX 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.
{"title":"Temporal variability of ozone and its precursors at tropical megacity, Bengaluru, India: Effect of volatile organic compounds and meteorology","authors":"G. Dhanya , T.S. Pranesha , Sandip Nivdange , Kamsali Nagaraja , B.S. Murthy , D.M. Chate , Gufran Beig , 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 (O<sub>3</sub>) and its precursors (NO, NO<sub>2</sub>, NOx) were taken over Bengaluru, a southern megacity, India, for 4 years period between January 2015 and December 2018. The seasonal variations of O<sub>3</sub>, NO, NO<sub>2</sub>, and NOx have been analysed to understand the short-term variability of the pollutants at this site. The magnitude of O<sub>3</sub> 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 NO<sub>2</sub> and NO<sub>x</sub> showed the highest (41.75, 50.42 ppbv) in the winter season. The lowest concentrations of NO (5.70 ppbv), NO<sub>2</sub> (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<sub>X</sub> ratio as a photochemical measure. This ratio indicates that the study region is NO<sub>X</sub> 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 O<sub>3</sub> 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 NO<sub>2</sub> 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}
Pub Date : 2024-12-01DOI: 10.1016/j.jastp.2024.106389
A. Kalyan Teja , M. Venkat Ratnam , S. Vijaya Bhaskara Rao
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.
{"title":"Mean winds and tidal variability from troposphere to the thermosphere retrieved from combined ground based and space borne measurements","authors":"A. Kalyan Teja , M. Venkat Ratnam , 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}
Pub Date : 2024-12-01DOI: 10.1016/j.jastp.2024.106393
Ganime Tuğba Önder
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.
{"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 (SF<sub>6</sub>) 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 SF<sub>6</sub> 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 R<sup>2</sup>, RMSE, NSE, MAE and MAPE%. The findings of this research highlight a continuous upward trend in SF<sub>6</sub> 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 SF<sub>6</sub> gas emissions. The LSTM model generally outperformed SARIMA and GRU models, having the lowest MAPE (0.003%), MAE (0.0003), RMSE (0.0003), and R<sup>2</sup> (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 SF<sub>6</sub> 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}
Pub Date : 2024-12-01DOI: 10.1016/j.jastp.2024.106395
A.P. Nickolaenko
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 f1 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.
{"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><sub>1</sub> 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}
Pub Date : 2024-12-01DOI: 10.1016/j.jastp.2024.106391
A.V. Ivanovskiy
The mechanism of a stepped leader not related to processes in the cloud is considered. The average leader speed is determined by the formation of a channel due to heating of one of the space stems in the electric field of the streamer corona. If the drift speed of the electrons in the formed channel is higher than the leader propagation speed, a drift wave arises which catches up with the boundary of the streamer zone. The electric field growth leads to a formation of the stepped leader. The mechanism is realized in case of a negative leader. Realism of this scenario has been checked by numerical simulations. For the negative leader the formation of the step with parameters close to those for natural leaders has been obtained. The estimated maximum speed of the electron drift at the stage of channel formation, which exceeds the negative leader propagation speed observed in the experiments, counts in favor of the above ideas.
{"title":"Mechanism of a stepped leader in a negative lightning","authors":"A.V. Ivanovskiy","doi":"10.1016/j.jastp.2024.106391","DOIUrl":"10.1016/j.jastp.2024.106391","url":null,"abstract":"<div><div>The mechanism of a stepped leader not related to processes in the cloud is considered. The average leader speed is determined by the formation of a channel due to heating of one of the space stems in the electric field of the streamer corona. If the drift speed of the electrons in the formed channel is higher than the leader propagation speed, a drift wave arises which catches up with the boundary of the streamer zone. The electric field growth leads to a formation of the stepped leader. The mechanism is realized in case of a negative leader. Realism of this scenario has been checked by numerical simulations. For the negative leader the formation of the step with parameters close to those for natural leaders has been obtained. The estimated maximum speed of the electron drift at the stage of channel formation, which exceeds the negative leader propagation speed observed in the experiments, counts in favor of the above ideas.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106391"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744320","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}
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.
{"title":"Modeling of Zenith Tropospheric Delay using ERA5 data over East African region","authors":"Geoffrey Andima , Richard Cliffe Ssenyunzi , Emirant Bertillas Amabayo , Alessandra Mascitelli , 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}
Pub Date : 2024-12-01DOI: 10.1016/j.jastp.2024.106392
Gerrit de Leeuw , Ronald van der A , Jianhui Bai , Mirjam den Hoed , Jieying Ding , Jianping Guo , Zhengqiang Li , Ying Zhang , Cheng Fan , Kai Qin , Selviga Sinnathamby , Sarah Safieddine , Costas Varotsos , Yong Xue , Yan Yin , Qianqian Zhang , Xin Zhang , XingYing Zhang , Xiumei Zhang
Air Quality (AQ) is determined by the concentrations of aerosols and trace gases. Aerosol concentration is measured by the mass concentration of particles smaller than 2.5 μm (PM2.5) or 10 μm (PM10), while trace gases include ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). Ammonia (NH3) and (biogenic) volatile organic compounds ((B)VOCs) also play an important role in atmospheric chemistry affecting the concentrations of trace gases and ultimately AQ. This study focuses on various aspects of AQ in China, utilizing remote sensing data from satellite and ground-based sensors to obtain information on PM emissions and concentrations and AQ-relevant trace gases. This research was conducted within the framework of the ESA/NRSCC MOST collaboration project Dragon 5, as part of the EMPAC (Exploitation of satellite remote sensing to enhance our comprehension of the Mechanisms and Processes influencing Air quality in China) project. It summarizes findings on four main topics: (1) Retrieval of trace gas concentrations and aerosol products from satellite data, validation using ground-based reference data, and interpretation of results in terms of AQ effects, such as the conversion of column-integrated properties to near-surface concentrations; (2) Determination of trace gases emissions relevant to AQ, using satellite data and models; (3) Analysis of time series data on trace gases and aerosols to assess the impact of emission reduction policies on AQ improvement; (4) Research contributing to a deeper understanding of mechanisms and processes affecting atmospheric composition about AQ.
{"title":"Remote sensing of air pollutants in China to study the effects of emission reduction policies on air quality","authors":"Gerrit de Leeuw , Ronald van der A , Jianhui Bai , Mirjam den Hoed , Jieying Ding , Jianping Guo , Zhengqiang Li , Ying Zhang , Cheng Fan , Kai Qin , Selviga Sinnathamby , Sarah Safieddine , Costas Varotsos , Yong Xue , Yan Yin , Qianqian Zhang , Xin Zhang , XingYing Zhang , Xiumei Zhang","doi":"10.1016/j.jastp.2024.106392","DOIUrl":"10.1016/j.jastp.2024.106392","url":null,"abstract":"<div><div>Air Quality (AQ) is determined by the concentrations of aerosols and trace gases. Aerosol concentration is measured by the mass concentration of particles smaller than 2.5 μm (PM2.5) or 10 μm (PM10), while trace gases include ozone (O<sub>3</sub>), nitrogen dioxide (NO<sub>2</sub>), sulfur dioxide (SO<sub>2</sub>), and carbon monoxide (CO). Ammonia (NH<sub>3</sub>) and (biogenic) volatile organic compounds ((B)VOCs) also play an important role in atmospheric chemistry affecting the concentrations of trace gases and ultimately AQ. This study focuses on various aspects of AQ in China, utilizing remote sensing data from satellite and ground-based sensors to obtain information on PM emissions and concentrations and AQ-relevant trace gases. This research was conducted within the framework of the ESA/NRSCC MOST collaboration project Dragon 5, as part of the EMPAC (Exploitation of satellite remote sensing to enhance our comprehension of the Mechanisms and Processes influencing Air quality in China) project. It summarizes findings on four main topics: (1) Retrieval of trace gas concentrations and aerosol products from satellite data, validation using ground-based reference data, and interpretation of results in terms of AQ effects, such as the conversion of column-integrated properties to near-surface concentrations; (2) Determination of trace gases emissions relevant to AQ, using satellite data and models; (3) Analysis of time series data on trace gases and aerosols to assess the impact of emission reduction policies on AQ improvement; (4) Research contributing to a deeper understanding of mechanisms and processes affecting atmospheric composition about AQ.</div></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106392"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 : 2024-12-01DOI: 10.1016/j.jastp.2024.106368
Inez S. Batista, Livia Alves, Clezio De Nardin, Sergio Dasso, Juan A. Valdivia
{"title":"Preface to the special issue “Recent advances in Space Geophysics including COLAGE”","authors":"Inez S. Batista, Livia Alves, Clezio De Nardin, Sergio Dasso, Juan A. Valdivia","doi":"10.1016/j.jastp.2024.106368","DOIUrl":"10.1016/j.jastp.2024.106368","url":null,"abstract":"","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":"265 ","pages":"Article 106368"},"PeriodicalIF":1.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151975","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}
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