Gang Zheng, Guanghui Wei, Fanghong Han, Yan Cao, Fan Gao
Research on evapotranspiration and its drivers in the Aksu River Basin from the perspectives of climate change and land use is of great significance for promoting the efficient use and precise allocation of its water resources. Theil-Sen median trend analysis (T-S) and the Mann–Kendall nonparametric test (M-K), in addition to correlation analysis, partial correlation analysis, complex correlation analysis, and driving-factor zoning principles, were used to examine the characteristics of the spatiotemporal changes in evapotranspiration and to explore the driving mechanism of the changes in evapotranspiration. The results indicated that the range of fluctuations in the multiyear average evapotranspiration in the Aksu River Basin from 2001 to 2020 was between 481.58 and 772.37 mm/a, which showed the spatial distribution characteristics of being high in the west and central part of the basin, and low in the north and south of the basin. The positive correlation between evapotranspiration and precipitation was stronger, and the negative correlations with temperature and relative humidity were stronger. The change in evapotranspiration in cultivated land is mainly driven by precipitation and relative humidity × precipitation; for grassland, the main drivers were relative humidity and precipitation × relative humidity; for woodland, the main drivers were relative humidity and other climatic factors; and for other land types, the main drivers were other climatic factors.
{"title":"Study on the Response Mechanism of Climate and Land Use Change to Evapotranspiration in Aksu River Basin","authors":"Gang Zheng, Guanghui Wei, Fanghong Han, Yan Cao, Fan Gao","doi":"10.3390/atmos15091055","DOIUrl":"https://doi.org/10.3390/atmos15091055","url":null,"abstract":"Research on evapotranspiration and its drivers in the Aksu River Basin from the perspectives of climate change and land use is of great significance for promoting the efficient use and precise allocation of its water resources. Theil-Sen median trend analysis (T-S) and the Mann–Kendall nonparametric test (M-K), in addition to correlation analysis, partial correlation analysis, complex correlation analysis, and driving-factor zoning principles, were used to examine the characteristics of the spatiotemporal changes in evapotranspiration and to explore the driving mechanism of the changes in evapotranspiration. The results indicated that the range of fluctuations in the multiyear average evapotranspiration in the Aksu River Basin from 2001 to 2020 was between 481.58 and 772.37 mm/a, which showed the spatial distribution characteristics of being high in the west and central part of the basin, and low in the north and south of the basin. The positive correlation between evapotranspiration and precipitation was stronger, and the negative correlations with temperature and relative humidity were stronger. The change in evapotranspiration in cultivated land is mainly driven by precipitation and relative humidity × precipitation; for grassland, the main drivers were relative humidity and precipitation × relative humidity; for woodland, the main drivers were relative humidity and other climatic factors; and for other land types, the main drivers were other climatic factors.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"68 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190267","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}
In this paper, we introduce a comprehensive solution aimed at enhancing our understanding of three-dimensional atmospheric pollutant dispersion. This innovative solution involves the development of a generalized model that extends previous research and is applicable to all parameterization schemes of these equations, including wind speed profiles and turbulent diffusion coefficients, while incorporating the dry deposition criterion. Our methodology involves subdividing the atmospheric boundary layer into distinct sub-layers, which facilitates a detailed examination of pollutant dispersion dynamics. Extensive validation with data from the Hanford experiment has demonstrated the accuracy of this solution in simulating pollutant concentrations. The results demonstrate that there is a strong correlation between the projected and observed concentrations, underscoring the statistical reliability of our approach. This validation situates the statistical indices of our solution within an acceptable range, confirming its accuracy in predicting atmospheric pollutant dispersion. These findings thus establish our solution as a valid and effective method for studying complex environmental phenomena.
{"title":"Generalized 3D Model of Crosswind Concentrations and Deposition in the Atmospheric Boundary Layer","authors":"Mehdi Farhane, Otmane Souhar","doi":"10.3390/atmos15091054","DOIUrl":"https://doi.org/10.3390/atmos15091054","url":null,"abstract":"In this paper, we introduce a comprehensive solution aimed at enhancing our understanding of three-dimensional atmospheric pollutant dispersion. This innovative solution involves the development of a generalized model that extends previous research and is applicable to all parameterization schemes of these equations, including wind speed profiles and turbulent diffusion coefficients, while incorporating the dry deposition criterion. Our methodology involves subdividing the atmospheric boundary layer into distinct sub-layers, which facilitates a detailed examination of pollutant dispersion dynamics. Extensive validation with data from the Hanford experiment has demonstrated the accuracy of this solution in simulating pollutant concentrations. The results demonstrate that there is a strong correlation between the projected and observed concentrations, underscoring the statistical reliability of our approach. This validation situates the statistical indices of our solution within an acceptable range, confirming its accuracy in predicting atmospheric pollutant dispersion. These findings thus establish our solution as a valid and effective method for studying complex environmental phenomena.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"74 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190270","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}
A better understanding of the spatiotemporal variation characteristics of rainfall erosivity and effects of extreme rainfall events on soil erosion is the basis for improved water resource planning, protection, and ecological restoration in the Qinling Mountains. Using long-term daily precipitation data from 19 national standard meteorological stations from 1957 to 2018, the spatiotemporal variation trend of rainfall erosivity was explored. A linear regression analysis method was used to detect trends in rainfall erosivity. The spatial pattern of rainfall erosivity, which is based on annual, seasonal, and extreme rainfall indices, was analyzed via a geospatial interpolation method. Effects of natural factors and human activities on soil erosion at different stages were examined via the double cumulative curve method. The average annual rainfall erosivity in the Shangluo area is 2306 MJ mm ha−1 h−1 year−1 and generally displays a gradual decreasing trend from southeast to northwest. Over the last 60 years, the annual R exhibited a nonsignificant increasing trend (p > 0.05). Overall, rainfall erosivity showed a phased trend with an increasing trend after 2000. Rainfall erosivity from June to September accounts for 78.5% of the annual total, while the annual R is mainly determined by a few rainfall events during the year. RX1d and RX5d account for 20–40% and 60–80%, respectively, of the total annual R and are likely to result in severe soil erosion in sloping cultivated land areas, agricultural lands, and dirt roads with continued climate change. Implementation of the National Natural Forest Protection Project and the ‘Grain for Green’ Project significantly reduced the intensity and scope of soil erosion in the area. This study aids in understanding the ecohydrological processes and soil erosion and sediment transport characteristics in the Qinling Mountains and promotes water resource protection and management along the middle route of the South-to-North Water Diversion Project.
{"title":"Spatiotemporal Trends and Variations in Rainfall Erosivity in the East Qinling Mountains and the Environmental Impacts","authors":"Xiaoming Xu","doi":"10.3390/atmos15091050","DOIUrl":"https://doi.org/10.3390/atmos15091050","url":null,"abstract":"A better understanding of the spatiotemporal variation characteristics of rainfall erosivity and effects of extreme rainfall events on soil erosion is the basis for improved water resource planning, protection, and ecological restoration in the Qinling Mountains. Using long-term daily precipitation data from 19 national standard meteorological stations from 1957 to 2018, the spatiotemporal variation trend of rainfall erosivity was explored. A linear regression analysis method was used to detect trends in rainfall erosivity. The spatial pattern of rainfall erosivity, which is based on annual, seasonal, and extreme rainfall indices, was analyzed via a geospatial interpolation method. Effects of natural factors and human activities on soil erosion at different stages were examined via the double cumulative curve method. The average annual rainfall erosivity in the Shangluo area is 2306 MJ mm ha−1 h−1 year−1 and generally displays a gradual decreasing trend from southeast to northwest. Over the last 60 years, the annual R exhibited a nonsignificant increasing trend (p > 0.05). Overall, rainfall erosivity showed a phased trend with an increasing trend after 2000. Rainfall erosivity from June to September accounts for 78.5% of the annual total, while the annual R is mainly determined by a few rainfall events during the year. RX1d and RX5d account for 20–40% and 60–80%, respectively, of the total annual R and are likely to result in severe soil erosion in sloping cultivated land areas, agricultural lands, and dirt roads with continued climate change. Implementation of the National Natural Forest Protection Project and the ‘Grain for Green’ Project significantly reduced the intensity and scope of soil erosion in the area. This study aids in understanding the ecohydrological processes and soil erosion and sediment transport characteristics in the Qinling Mountains and promotes water resource protection and management along the middle route of the South-to-North Water Diversion Project.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"392 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190299","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}
Due to the complex nature of the built environment, urban wind flow is unpredictable and characterised by high levels of turbulence and low mean wind speed. Yet, there is a potential for harnessing urban wind power by carefully integrating wind turbines within the built environment at the optimum locations. This requires a thorough investigation of wind resources to use the suitable wind turbine technology at the correct location—thus, the need for an accurate assessment of wind resources at the proposed site. This paper reviews the commonly used wind assessment tools for the urban wind flow to identify the optimum tool to be used prior to integrating wind turbines in urban areas. In situ measurements, wind tunnel tests, and CFD simulations are analysed and reviewed through their advantages and disadvantages in assessing urban wind flows. The literature shows that CFD simulations are favoured over other most commonly used tools because the tool is relatively easier to use, more efficient in comparing alternative design solutions, and can effectively communicate data visually. The paper concludes with recommendations on best practice guidelines for using CFD simulation in assessing the wind flow within the built environment and emphasises the importance of validating CFD simulation results by other available tools to avoid any associated uncertainties.
{"title":"Analytical Review of Wind Assessment Tools for Urban Wind Turbine Applications","authors":"Islam Abohela, Raveendran Sundararajan","doi":"10.3390/atmos15091049","DOIUrl":"https://doi.org/10.3390/atmos15091049","url":null,"abstract":"Due to the complex nature of the built environment, urban wind flow is unpredictable and characterised by high levels of turbulence and low mean wind speed. Yet, there is a potential for harnessing urban wind power by carefully integrating wind turbines within the built environment at the optimum locations. This requires a thorough investigation of wind resources to use the suitable wind turbine technology at the correct location—thus, the need for an accurate assessment of wind resources at the proposed site. This paper reviews the commonly used wind assessment tools for the urban wind flow to identify the optimum tool to be used prior to integrating wind turbines in urban areas. In situ measurements, wind tunnel tests, and CFD simulations are analysed and reviewed through their advantages and disadvantages in assessing urban wind flows. The literature shows that CFD simulations are favoured over other most commonly used tools because the tool is relatively easier to use, more efficient in comparing alternative design solutions, and can effectively communicate data visually. The paper concludes with recommendations on best practice guidelines for using CFD simulation in assessing the wind flow within the built environment and emphasises the importance of validating CFD simulation results by other available tools to avoid any associated uncertainties.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"23 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190300","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}
Izabela Pawlak, Janusz Krzyścin, Janusz Jarosławski
Surface ozone (O3) and nitrogen oxides (NOx = NO + NO2) measured at the rural station in Belsk (51.83° N, 20.79° E), Poland, over the period of 1995−2023, were examined for long-term variability of O3 and its relationship to changes in the air temperature and NOx. Negative and positive trends were found for the 95th and 5th percentile, respectively, in the O3 data. A weak positive correlation (statistically significant) of 0.33 was calculated between O3 and the temperature averaged from sunrise to sunset during the photoactive part of the year (April–September). Recently, O3 maxima have become less sensitive to temperature changes, reducing the incidence of photochemical smog. The ozone–climate penalty factor decreased from 4.4 µg/m3/°C in the 1995–2004 period to 3.9 µg/m3/°C in the 2015−2023 period. The relationship between Ox (O3 + NO2) and NOx concentrations averaged from sunrise to sunset determined the local and regional contribution to Ox variability. The seasonal local and regional contributions remained unchanged in the period of 1995−2023, stabilizing the average O3 level at Belsk. “NOx-limited” and “VOC-limited” photochemical regimes prevailed in the summer and autumn, respectively. For many winter and spring seasons between 1995 and 2023, the type of photochemical regime could not be accurately determined, making it difficult to build an effective O3 mitigation policy.
{"title":"Long-Term Variability of Surface Ozone and Its Associations with NOx and Air Temperature Changes from Air Quality Monitoring at Belsk, Poland, 1995–2023","authors":"Izabela Pawlak, Janusz Krzyścin, Janusz Jarosławski","doi":"10.3390/atmos15080960","DOIUrl":"https://doi.org/10.3390/atmos15080960","url":null,"abstract":"Surface ozone (O3) and nitrogen oxides (NOx = NO + NO2) measured at the rural station in Belsk (51.83° N, 20.79° E), Poland, over the period of 1995−2023, were examined for long-term variability of O3 and its relationship to changes in the air temperature and NOx. Negative and positive trends were found for the 95th and 5th percentile, respectively, in the O3 data. A weak positive correlation (statistically significant) of 0.33 was calculated between O3 and the temperature averaged from sunrise to sunset during the photoactive part of the year (April–September). Recently, O3 maxima have become less sensitive to temperature changes, reducing the incidence of photochemical smog. The ozone–climate penalty factor decreased from 4.4 µg/m3/°C in the 1995–2004 period to 3.9 µg/m3/°C in the 2015−2023 period. The relationship between Ox (O3 + NO2) and NOx concentrations averaged from sunrise to sunset determined the local and regional contribution to Ox variability. The seasonal local and regional contributions remained unchanged in the period of 1995−2023, stabilizing the average O3 level at Belsk. “NOx-limited” and “VOC-limited” photochemical regimes prevailed in the summer and autumn, respectively. For many winter and spring seasons between 1995 and 2023, the type of photochemical regime could not be accurately determined, making it difficult to build an effective O3 mitigation policy.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"43 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944028","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 ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based on GNSS-TEC data from 2015 and 2019. The electron density profiles and NmF2 calculated by the IRI-2016 model (upda-IRI-2016) driven by the updated IG12 value (IG-up) were evaluated for their accuracy using ionosonde observations and COSMIC inversion data. The experiments show that both the electron density profiles and NmF2 calculated by upda-IRI-2016 driven by IG-up show significant optimization effects, compared to the IRI-2016 model driven by IG12. For electron density, the precision improvement (PI) for both MAE and RMSE at the Beijing station exceed 31.2% in January 2015 and 16.0% in January 2019. While the PI of MAE and RMSE at the Wuhan station, which is located at a lower latitude, both exceed 32.5% in January 2015, both exceed 42.1% in January 2019, which is significantly higher than that of the Beijing station. In 2015, the PI of MAE and RMSE compared with COSMIC are both higher than 20%. For NmF2, the PI is greater for low solar activity years and low latitude stations, with the Wuhan station showing a PI of more than 11.7% in January 2019 compared to January 2015. The PI compared to COSMIC was higher than 17.2% in 2015.
电离层是影响无线电信号通信的重要误差源之一。国际参考电离层（IRI）模型是描述电离层参数的常用模型。根据 2015 年和 2019 年的 GNSS-TEC 数据，对 IRI-2016 模型的驱动参数 IG12 进行了优化更新。利用电离层观测数据和COSMIC反演数据，评估了IRI-2016模型（upda-IRI-2016）在更新的IG12值（IG-up）驱动下计算的电子密度剖面和NmF2的准确性。实验表明，与IG12驱动的IRI-2016模型相比，IG-up驱动的upda-IRI-2016计算的电子密度剖面和NmF2都有显著的优化效果。在电子密度方面，北京站的 MAE 和 RMSE 精度改进（PI）在 2015 年 1 月和 2019 年 1 月分别超过 31.2% 和 16.0%。而纬度较低的武汉站的 MAE 和 RMSE 的 PI 在 2015 年 1 月均超过 32.5%，2019 年 1 月均超过 42.1%，明显高于北京站。与 COSMIC 相比，2015 年 MAE 和 RMSE 的 PI 均高于 20%。对于 NmF2，低太阳活动年和低纬度站点的 PI 更大，武汉站 2019 年 1 月与 2015 年 1 月相比 PI 超过 11.7%。与 COSMIC 相比，2015 年的 PI 高于 17.2%。
{"title":"Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density","authors":"Jing Peng, Yunbin Yuan, Yanwen Liu, Hongxing Zhang, Ting Zhang, Yifan Wang, Zelin Dai","doi":"10.3390/atmos15080958","DOIUrl":"https://doi.org/10.3390/atmos15080958","url":null,"abstract":"The ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based on GNSS-TEC data from 2015 and 2019. The electron density profiles and NmF2 calculated by the IRI-2016 model (upda-IRI-2016) driven by the updated IG12 value (IG-up) were evaluated for their accuracy using ionosonde observations and COSMIC inversion data. The experiments show that both the electron density profiles and NmF2 calculated by upda-IRI-2016 driven by IG-up show significant optimization effects, compared to the IRI-2016 model driven by IG12. For electron density, the precision improvement (PI) for both MAE and RMSE at the Beijing station exceed 31.2% in January 2015 and 16.0% in January 2019. While the PI of MAE and RMSE at the Wuhan station, which is located at a lower latitude, both exceed 32.5% in January 2015, both exceed 42.1% in January 2019, which is significantly higher than that of the Beijing station. In 2015, the PI of MAE and RMSE compared with COSMIC are both higher than 20%. For NmF2, the PI is greater for low solar activity years and low latitude stations, with the Wuhan station showing a PI of more than 11.7% in January 2019 compared to January 2015. The PI compared to COSMIC was higher than 17.2% in 2015.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"8 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944019","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}
Dan Ye, Xin Wang, Yong Han, Yurong Zhang, Li Dong, Hao Luo, Xinxin Xie, Danya Xu
In the current environment of climate change, the precipitation situation of marine islands is particularly valued. So, this study explores precipitation characteristics and mechanisms over Sri Lanka in the background of the western Indian Ocean using satellite and reanalysis datasets based on 40 years (from 1981 to 2020). The results show that the highest precipitation occurs between October and December, accounting for 46.3% of the entire year. The Indian Ocean sea surface temperature warming after 2002 significantly influences precipitation patterns. Particularly during the Second Inter-Monsoon, the western Indian Ocean warming induces an east–west zonal sea surface temperature gradient, leading to low-level circulation and westerly wind anomalies. This, in turn, results in increased precipitation in Sri Lanka between October and December. This study used the Trend-Free Pre-Whitening Mann–Kendall test and Sen’s slope estimator to study nine extreme precipitation indices, identifying a significant upward trend in extreme precipitation events in the Jaffna, arid northern Sri Lanka, peaking on 9 November 2021. This extreme event is due to the influence of weather systems like the Siberian High and intense convective activities, transporting substantial moisture to Jaffna from the Indian Ocean, the Arabian Sea, and the Bay of Bengal during winter. The findings highlight the impact of sea surface temperature warming anomalies in the western Indian Ocean and extreme precipitation events, anticipated to be more accentuated during Sri Lanka’s monsoon season. This research provides valuable insights into the variability of tropical precipitation, offering a scientific basis for the sustainable development of marine islands.
{"title":"Precipitation Characteristics and Mechanisms over Sri Lanka against the Background of the Western Indian Ocean: 1981–2020","authors":"Dan Ye, Xin Wang, Yong Han, Yurong Zhang, Li Dong, Hao Luo, Xinxin Xie, Danya Xu","doi":"10.3390/atmos15080962","DOIUrl":"https://doi.org/10.3390/atmos15080962","url":null,"abstract":"In the current environment of climate change, the precipitation situation of marine islands is particularly valued. So, this study explores precipitation characteristics and mechanisms over Sri Lanka in the background of the western Indian Ocean using satellite and reanalysis datasets based on 40 years (from 1981 to 2020). The results show that the highest precipitation occurs between October and December, accounting for 46.3% of the entire year. The Indian Ocean sea surface temperature warming after 2002 significantly influences precipitation patterns. Particularly during the Second Inter-Monsoon, the western Indian Ocean warming induces an east–west zonal sea surface temperature gradient, leading to low-level circulation and westerly wind anomalies. This, in turn, results in increased precipitation in Sri Lanka between October and December. This study used the Trend-Free Pre-Whitening Mann–Kendall test and Sen’s slope estimator to study nine extreme precipitation indices, identifying a significant upward trend in extreme precipitation events in the Jaffna, arid northern Sri Lanka, peaking on 9 November 2021. This extreme event is due to the influence of weather systems like the Siberian High and intense convective activities, transporting substantial moisture to Jaffna from the Indian Ocean, the Arabian Sea, and the Bay of Bengal during winter. The findings highlight the impact of sea surface temperature warming anomalies in the western Indian Ocean and extreme precipitation events, anticipated to be more accentuated during Sri Lanka’s monsoon season. This research provides valuable insights into the variability of tropical precipitation, offering a scientific basis for the sustainable development of marine islands.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"198 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141943964","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}
It is well established that the reaction cycles involving some halogenated alkanes (so-called ozone-depleting substances—ODSs) contribute to the depletion of ozone in the stratosphere, prompting the Montreal Protocol (initially signed in 1987), and later amendments. The Protocol called for the scheduled phase-out of ODSs, including chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), carbon tetrachloride (CCl4), halon, methyl chloroform (CH3CCl3), methyl chloride (CH3Cl), and even hydrofluorocarbons (HFCs). In view of the urgent importance of ozone layer protection to the global ecological environment, the Taiwanese government has taken regulatory actions to reduce ODS consumption since 1993, through the joint venture of the central competent authorities. Under the government’s regulatory requirements, and the industry’s efforts to adopt both alternatives to ODSs and abatement technologies, the phase-out of some ODSs (i.e., CFCs, CCl4, halon, and CH3CCl3) was achieved prior to 2010. The consumption of HCFCs and methyl chloride has significantly declined over the past three decades (1993–2022). However, HFC emissions indicated a V-type variation during this period. Due to local production and extensive use of HFCs in Taiwan, the country’s emissions increased from 663 kilotons of carbon dioxide equivalents (CO2eq) in 1993 to 2330 kilotons of CO2eq in 2001, and then decreased to 373 kilotons of CO2eq in 2011. Since then, the emissions of HFCs largely used as the alternatives to ODSs showed an upward trend, increasing to 1555 kilotons of CO2eq in 2022. To be in compliance with the Kigali Amendment (KA-2015) to the Montreal Protocol for mitigating global warming, the Taiwanese government has taken regulatory actions to reduce the consumption of some HFC substances with high global warming potential (GWP) under the authorization of the Climate Change Response Act in 2023, aiming at an 80% reduction by 2045 of the baseline consumption in 2024.
{"title":"Environmental Policies and Countermeasures for the Phase-Out of Ozone-Depleting Substances (ODSs) over the Last 30 Years: A Case Study in Taiwan","authors":"Wen-Tien Tsai","doi":"10.3390/atmos15080961","DOIUrl":"https://doi.org/10.3390/atmos15080961","url":null,"abstract":"It is well established that the reaction cycles involving some halogenated alkanes (so-called ozone-depleting substances—ODSs) contribute to the depletion of ozone in the stratosphere, prompting the Montreal Protocol (initially signed in 1987), and later amendments. The Protocol called for the scheduled phase-out of ODSs, including chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), carbon tetrachloride (CCl4), halon, methyl chloroform (CH3CCl3), methyl chloride (CH3Cl), and even hydrofluorocarbons (HFCs). In view of the urgent importance of ozone layer protection to the global ecological environment, the Taiwanese government has taken regulatory actions to reduce ODS consumption since 1993, through the joint venture of the central competent authorities. Under the government’s regulatory requirements, and the industry’s efforts to adopt both alternatives to ODSs and abatement technologies, the phase-out of some ODSs (i.e., CFCs, CCl4, halon, and CH3CCl3) was achieved prior to 2010. The consumption of HCFCs and methyl chloride has significantly declined over the past three decades (1993–2022). However, HFC emissions indicated a V-type variation during this period. Due to local production and extensive use of HFCs in Taiwan, the country’s emissions increased from 663 kilotons of carbon dioxide equivalents (CO2eq) in 1993 to 2330 kilotons of CO2eq in 2001, and then decreased to 373 kilotons of CO2eq in 2011. Since then, the emissions of HFCs largely used as the alternatives to ODSs showed an upward trend, increasing to 1555 kilotons of CO2eq in 2022. To be in compliance with the Kigali Amendment (KA-2015) to the Montreal Protocol for mitigating global warming, the Taiwanese government has taken regulatory actions to reduce the consumption of some HFC substances with high global warming potential (GWP) under the authorization of the Climate Change Response Act in 2023, aiming at an 80% reduction by 2045 of the baseline consumption in 2024.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"197 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944025","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}
To improve the forecast accuracy of heavy precipitation, re-forecasts are conducted for the Henan 21.7 rainstorm. The Intermediate Complexity Atmospheric Research Model (ICAR) and the Weather Research and Forecasting Model (WRF) with a 1 km horizontal grid spacing are used for the re-forecasts. The results indicate that heavy precipitation forecasted by ICAR primarily accumulates on the windward slopes of the mountains. In contrast, some severe precipitation forecasted by WRF is beyond the mountains. The main difference between ICAR and WRF is that ICAR excludes the “impacts of physical processes on winds and the nonlinear interactions between the small resolvable-scale disturbances” (briefed as the “physical–dynamical interactions”). Thus, heavy precipitation beyond the mountains is attributed to the “physical–dynamical interactions”. Furthermore, severe precipitation on the windward slopes of the mountains typically aligns with the observations, whereas heavy rainfall beyond the mountains seldom matches the observations. Therefore, severe precipitation on the windward slopes of (beyond) the mountains is more (less) predictable. Based on these findings and theoretical thinking about the predictability of severe precipitation, a scheme of using the ICAR’s prediction to adjust the WRF’s prediction is proposed, thereby improving the forecast accuracy of heavy rainfall.
{"title":"The Application of an Intermediate Complexity Atmospheric Research Model in the Forecasting of the Henan 21.7 Rainstorm","authors":"Xingbao Wang, Qun Xu, Xiajun Deng, Hongjie Zhang, Qianhong Tang, Tingting Zhou, Fengcai Qi, Wenwu Peng","doi":"10.3390/atmos15080959","DOIUrl":"https://doi.org/10.3390/atmos15080959","url":null,"abstract":"To improve the forecast accuracy of heavy precipitation, re-forecasts are conducted for the Henan 21.7 rainstorm. The Intermediate Complexity Atmospheric Research Model (ICAR) and the Weather Research and Forecasting Model (WRF) with a 1 km horizontal grid spacing are used for the re-forecasts. The results indicate that heavy precipitation forecasted by ICAR primarily accumulates on the windward slopes of the mountains. In contrast, some severe precipitation forecasted by WRF is beyond the mountains. The main difference between ICAR and WRF is that ICAR excludes the “impacts of physical processes on winds and the nonlinear interactions between the small resolvable-scale disturbances” (briefed as the “physical–dynamical interactions”). Thus, heavy precipitation beyond the mountains is attributed to the “physical–dynamical interactions”. Furthermore, severe precipitation on the windward slopes of the mountains typically aligns with the observations, whereas heavy rainfall beyond the mountains seldom matches the observations. Therefore, severe precipitation on the windward slopes of (beyond) the mountains is more (less) predictable. Based on these findings and theoretical thinking about the predictability of severe precipitation, a scheme of using the ICAR’s prediction to adjust the WRF’s prediction is proposed, thereby improving the forecast accuracy of heavy rainfall.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"10 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944020","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}
Homogenization of the time series of observed climatic data aims to remove non-climatic biases caused by technical changes during the history of the climate observations. The spatial redundancy of climate information helps to recognize station-specific inhomogeneities with statistical methods, but the correct detection and removal of inhomogeneity biases is generally not easy for the combined effects of individual inhomogeneities. In a homogenization procedure, several time series of a given climatic variable observed in one climatic region are usually homogenized together via a large number of spatial comparisons between them. Such procedures are called relative homogenization. A relative homogenization procedure may include one or more homogenization cycles where a cycle includes the steps of time series comparison, inhomogeneity detection and corrections for inhomogeneities, and they may include other steps like the filtering of outlier values or spatial interpolations for infilling data gaps. Relative homogenization methods differ according to the number and content of the individual homogenization cycles, the procedure for the time series comparisons, the statistical inhomogeneity detection method, the way of the inhomogeneity bias removal, among other specifics. Efficient homogenization needs the use of tested statistical methods to be included in partly or fully automated homogenization procedures. Due to the large number and high variety of homogenization experiments fulfilled in the Spanish MULTITEST project (2015–2017), its method comparison test results are still the most informative about the efficiencies of homogenization methods in use. This study presents a brief review of the advances in relative homogenization, recalls some key results of the MULTITEST project, and analyzes some theoretical aspects of successful homogenization.
{"title":"Relative Homogenization of Climatic Time Series","authors":"Peter Domonkos","doi":"10.3390/atmos15080957","DOIUrl":"https://doi.org/10.3390/atmos15080957","url":null,"abstract":"Homogenization of the time series of observed climatic data aims to remove non-climatic biases caused by technical changes during the history of the climate observations. The spatial redundancy of climate information helps to recognize station-specific inhomogeneities with statistical methods, but the correct detection and removal of inhomogeneity biases is generally not easy for the combined effects of individual inhomogeneities. In a homogenization procedure, several time series of a given climatic variable observed in one climatic region are usually homogenized together via a large number of spatial comparisons between them. Such procedures are called relative homogenization. A relative homogenization procedure may include one or more homogenization cycles where a cycle includes the steps of time series comparison, inhomogeneity detection and corrections for inhomogeneities, and they may include other steps like the filtering of outlier values or spatial interpolations for infilling data gaps. Relative homogenization methods differ according to the number and content of the individual homogenization cycles, the procedure for the time series comparisons, the statistical inhomogeneity detection method, the way of the inhomogeneity bias removal, among other specifics. Efficient homogenization needs the use of tested statistical methods to be included in partly or fully automated homogenization procedures. Due to the large number and high variety of homogenization experiments fulfilled in the Spanish MULTITEST project (2015–2017), its method comparison test results are still the most informative about the efficiencies of homogenization methods in use. This study presents a brief review of the advances in relative homogenization, recalls some key results of the MULTITEST project, and analyzes some theoretical aspects of successful homogenization.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"36 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944027","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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