Pub Date : 2024-06-18DOI: 10.5194/egusphere-2024-1454
Mingxu Liu, Hitoshi Matsui, Douglas Hamilton, Sagar Rathod, Kara Lamb, Natalie Mahowald
Abstract. Atmospheric aerosol deposition acts as a major source of soluble (bioavailable) iron in open ocean regions where it limits phytoplankton growth and primary production. The aerosol size distribution of emitted iron particles, along with particle growth from mixing with other atmospheric components, is an important modulator of its long-range transport potential. There currently exists a large uncertainty in the particle size distribution of iron aerosol, and the role of aerosol size in shaping global soluble iron deposition is thus unclear. In this study, we couple a sophisticated microphysical, size-resolved aerosol model with an iron-speciated and -processing module to disentangle the impact of iron emission size distributions on soluble iron input to the ocean, with a focus on anthropogenic combustion and metal smelting sources. We first evaluate our model results against a global-scale flight measurement dataset for anthropogenic iron concentration and find that the different representations of iron size distribution at emission, as adopted in previous studies, introduces a variability in modeled iron concentrations over remote oceans of a factor of 10. Shifting the iron aerosol size distribution toward finer particle sizes (<1 μm) enables longer atmospheric lifetime (a doubling), promoting atmospheric processing that enhances the soluble iron deposition to ocean basins by up to 50 % on an annual basis. Importantly, the monthly enhancements reach 110 % and 80 % over the Southern Ocean and North Pacific Ocean, respectively. Compared with emission flux uncertainties, we find that iron emission size distribution plays an equally important role in regulating soluble iron deposition, especially to the remote oceans. Our findings provide implications for understanding the effects of atmospheric nutrients input on marine biogeochemistry, including but not limited to iron, phosphorus, and others.
{"title":"Representation of iron aerosol size distributions is critical in evaluating atmospheric soluble iron input to the ocean","authors":"Mingxu Liu, Hitoshi Matsui, Douglas Hamilton, Sagar Rathod, Kara Lamb, Natalie Mahowald","doi":"10.5194/egusphere-2024-1454","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1454","url":null,"abstract":"<strong>Abstract.</strong> Atmospheric aerosol deposition acts as a major source of soluble (bioavailable) iron in open ocean regions where it limits phytoplankton growth and primary production. The aerosol size distribution of emitted iron particles, along with particle growth from mixing with other atmospheric components, is an important modulator of its long-range transport potential. There currently exists a large uncertainty in the particle size distribution of iron aerosol, and the role of aerosol size in shaping global soluble iron deposition is thus unclear. In this study, we couple a sophisticated microphysical, size-resolved aerosol model with an iron-speciated and -processing module to disentangle the impact of iron emission size distributions on soluble iron input to the ocean, with a focus on anthropogenic combustion and metal smelting sources. We first evaluate our model results against a global-scale flight measurement dataset for anthropogenic iron concentration and find that the different representations of iron size distribution at emission, as adopted in previous studies, introduces a variability in modeled iron concentrations over remote oceans of a factor of 10. Shifting the iron aerosol size distribution toward finer particle sizes (<1 μm) enables longer atmospheric lifetime (a doubling), promoting atmospheric processing that enhances the soluble iron deposition to ocean basins by up to 50 % on an annual basis. Importantly, the monthly enhancements reach 110 % and 80 % over the Southern Ocean and North Pacific Ocean, respectively. Compared with emission flux uncertainties, we find that iron emission size distribution plays an equally important role in regulating soluble iron deposition, especially to the remote oceans. Our findings provide implications for understanding the effects of atmospheric nutrients input on marine biogeochemistry, including but not limited to iron, phosphorus, and others.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"1 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-18DOI: 10.5194/egusphere-2024-1715
Namrata Shanmukh Panji, Deborah F. McGlynn, Laura E. R. Barry, Todd M. Scanlon, Manuel T. Lerdau, Sally E. Pusede, Gabriel Isaacman-VanWertz
Abstract. Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated BVOC measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA for the 2020 year with emissions estimated by MEGANv3.2. The emissions were subjected to oxidation in a 0-D box-model (F0AM v4.3) to generate timeseries of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability of regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDFα-pinene=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using LDF=0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions-chemistry model constrained by regional concentrations of NOx and O3.
{"title":"Constraining Light Dependency in Modeled Emissions Through Comparison to Observed BVOC Concentrations in a Southeastern US Forest","authors":"Namrata Shanmukh Panji, Deborah F. McGlynn, Laura E. R. Barry, Todd M. Scanlon, Manuel T. Lerdau, Sally E. Pusede, Gabriel Isaacman-VanWertz","doi":"10.5194/egusphere-2024-1715","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1715","url":null,"abstract":"<strong>Abstract.</strong> Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated BVOC measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA for the 2020 year with emissions estimated by MEGANv3.2. The emissions were subjected to oxidation in a 0-D box-model (F0AM v4.3) to generate timeseries of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability of regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDF<sub>α-pinene</sub>=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using LDF=0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions-chemistry model constrained by regional concentrations of NO<sub>x</sub> and O<sub>3</sub>.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"23 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-17DOI: 10.5194/acp-24-6965-2024
Cheng Zheng, Yutian Wu, Mingfang Ting, Clara Orbe
Abstract. Trace gases and aerosols play a crucial role in shaping Arctic climate through their impacts on radiation and chemistry. The concentration of these substances over the Arctic is largely determined by long-range transport originating from midlatitude and tropical source regions. In this study, we explore how atmospheric circulation modulates the interannual variability of long-range transport into the Arctic by utilizing a chemistry–climate model. Idealized tracers, which have fixed lifetimes and spatially varying but temporally fixed surface emissions corresponding to the climatology of anthropogenic emissions of the year 2000, are employed to isolate the role of atmospheric transport from emission and chemistry in modulating interannual variability. Tracers emitted from different source regions are tagged to quantify their relative contributions. Model simulations reveal that tracers from Europe, East Asia, and North America contribute the most to Arctic tracer mass, followed by those from the Tibetan Plateau and South Asia, as well as the Middle East. These regional tracers are predominantly transported into the Arctic middle to upper troposphere, with the exception of tracers from Europe during winter, which are transported into the Arctic lower troposphere. Our analysis shows that the interannual variability of transport into the Arctic for each regional tracer is determined by the atmospheric circulation over the corresponding emission region; i.e., anomalous poleward and eastward winds over the source region promote transport into the Arctic. Considering tracers with global emissions, a southward shift of the midlatitude jet during winter favors increased transport into the Arctic, particularly for tracers emitted over Asia, aligning with previous studies. Comparisons of tracers with different lifetimes indicate that the interannual variability of shorter lifetime tracers is predominantly influenced by regional tracers with shorter transport pathways into the Arctic (e.g., Europe), while the interannual variability of longer lifetime tracers is more contributed by regional tracers with higher emissions (e.g., East Asia).
{"title":"Influence of atmospheric circulation on the interannual variability of transport from global and regional emissions into the Arctic","authors":"Cheng Zheng, Yutian Wu, Mingfang Ting, Clara Orbe","doi":"10.5194/acp-24-6965-2024","DOIUrl":"https://doi.org/10.5194/acp-24-6965-2024","url":null,"abstract":"Abstract. Trace gases and aerosols play a crucial role in shaping Arctic climate through their impacts on radiation and chemistry. The concentration of these substances over the Arctic is largely determined by long-range transport originating from midlatitude and tropical source regions. In this study, we explore how atmospheric circulation modulates the interannual variability of long-range transport into the Arctic by utilizing a chemistry–climate model. Idealized tracers, which have fixed lifetimes and spatially varying but temporally fixed surface emissions corresponding to the climatology of anthropogenic emissions of the year 2000, are employed to isolate the role of atmospheric transport from emission and chemistry in modulating interannual variability. Tracers emitted from different source regions are tagged to quantify their relative contributions. Model simulations reveal that tracers from Europe, East Asia, and North America contribute the most to Arctic tracer mass, followed by those from the Tibetan Plateau and South Asia, as well as the Middle East. These regional tracers are predominantly transported into the Arctic middle to upper troposphere, with the exception of tracers from Europe during winter, which are transported into the Arctic lower troposphere. Our analysis shows that the interannual variability of transport into the Arctic for each regional tracer is determined by the atmospheric circulation over the corresponding emission region; i.e., anomalous poleward and eastward winds over the source region promote transport into the Arctic. Considering tracers with global emissions, a southward shift of the midlatitude jet during winter favors increased transport into the Arctic, particularly for tracers emitted over Asia, aligning with previous studies. Comparisons of tracers with different lifetimes indicate that the interannual variability of shorter lifetime tracers is predominantly influenced by regional tracers with shorter transport pathways into the Arctic (e.g., Europe), while the interannual variability of longer lifetime tracers is more contributed by regional tracers with higher emissions (e.g., East Asia).","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"60 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-17DOI: 10.5194/egusphere-2024-1516
Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, Miao Zhang
Abstract. Four distinct retrieval algorithms, comprising two physics-based and two machine-learning (ML) approaches, have been developed to retrieve cloud base height (CBH) and its diurnal cycle from Himawari-8 geostationary satellite observations. Validations have been conducted using the joint CloudSat/CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) CBH products in 2017, ensuring independent assessments. Results show that the two ML-based algorithms exhibit markedly superior performance (with a correlation coefficient of R > 0.91 and an absolute bias of approximately 0.8 km) compared to the two physics-based algorithms. However, validations based on CBH data from the ground-based lidar at the Lijiang station in Yunnan province and the cloud radar at the Nanjiao station in Beijing, China, explicitly present contradictory outcomes (R < 0.60). An identifiable issue arises with significant underestimations in the retrieved CBH by both ML-based algorithms, leading to an inability to capture the diurnal cycle characteristics of CBH. The strong consistence observed between CBH derived from ML-based algorithms and the spaceborne active sensor may be attributed to utilizing the same dataset for training and validation, sourced from the CloudSat/CALIOP products. In contrast, the CBH derived from the optimal physics-based algorithm demonstrates the good agreement in diurnal variations of CBH with ground-based lidar/cloud radar observations during the daytime (with an R value of approximately 0.7). Therefore, the findings in this investigation from ground-based observations advocate for the more reliable and adaptable nature of physics-based algorithms in retrieving CBH from geostationary satellite measurements. Nevertheless, under ideal conditions, with an ample dataset of spaceborne cloud profiling radar observations encompassing the entire day for training purposes, the ML-based algorithms may hold promise in still delivering accurate CBH outputs.
摘要已开发出四种不同的检索算法，包括两种基于物理的方法和两种机器学习（ML）方法，用于从向日葵-8 号静止卫星观测数据中检索云底高度（CBH）及其昼夜周期。2017年，利用CloudSat/CALIOP（正交偏振云-气溶胶激光雷达）联合CBH产品进行了验证，以确保独立评估。结果表明，与基于物理的两种算法相比，基于 ML 的两种算法表现出明显的优越性能（相关系数为 R > 0.91，绝对偏差约为 0.8 公里）。然而，基于云南丽江站地基激光雷达和中国北京南郊站云雷达的 CBH 数据的验证结果（R< 0.60）却明显存在矛盾。一个明显的问题是，两种基于 ML 的算法都严重低估了获取的 CBH，导致无法捕捉 CBH 的昼夜周期特征。基于 ML 算法和机载主动传感器得出的 CBH 具有很强的一致性，这可能是由于使用了相同的数据集（来自 CloudSat/CALIOP 产品）进行训练和验证。相比之下，基于物理学的最优算法得出的 CBH 与地面激光雷达/云雷达在白天观测到的 CBH 日变化具有良好的一致性（R 值约为 0.7）。因此，这次地面观测的研究结果表明，基于物理的算法在从静止卫星测量结果中检索 CBH 方面更可靠，适应性更强。不过，在理想条件下，如果有足够的全天候空间云剖面雷达观测数据集作为训练，基于 ML 的算法仍有希望提供准确的 CBH 输出。
{"title":"Technical note: Applicability of physics-based and machine-learning-based algorithms of geostationary satellite in retrieving the diurnal cycle of cloud base height","authors":"Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, Miao Zhang","doi":"10.5194/egusphere-2024-1516","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1516","url":null,"abstract":"<strong>Abstract.</strong> Four distinct retrieval algorithms, comprising two physics-based and two machine-learning (ML) approaches, have been developed to retrieve cloud base height (CBH) and its diurnal cycle from Himawari-8 geostationary satellite observations. Validations have been conducted using the joint CloudSat/CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) CBH products in 2017, ensuring independent assessments. Results show that the two ML-based algorithms exhibit markedly superior performance (with a correlation coefficient of R > 0.91 and an absolute bias of approximately 0.8 km) compared to the two physics-based algorithms. However, validations based on CBH data from the ground-based lidar at the Lijiang station in Yunnan province and the cloud radar at the Nanjiao station in Beijing, China, explicitly present contradictory outcomes (R < 0.60). An identifiable issue arises with significant underestimations in the retrieved CBH by both ML-based algorithms, leading to an inability to capture the diurnal cycle characteristics of CBH. The strong consistence observed between CBH derived from ML-based algorithms and the spaceborne active sensor may be attributed to utilizing the same dataset for training and validation, sourced from the CloudSat/CALIOP products. In contrast, the CBH derived from the optimal physics-based algorithm demonstrates the good agreement in diurnal variations of CBH with ground-based lidar/cloud radar observations during the daytime (with an R value of approximately 0.7). Therefore, the findings in this investigation from ground-based observations advocate for the more reliable and adaptable nature of physics-based algorithms in retrieving CBH from geostationary satellite measurements. Nevertheless, under ideal conditions, with an ample dataset of spaceborne cloud profiling radar observations encompassing the entire day for training purposes, the ML-based algorithms may hold promise in still delivering accurate CBH outputs.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"8 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-17DOI: 10.5194/egusphere-2024-1393
Azzurra Spagnesi, Elena Barbaro, Matteo Feltracco, Federico Scoto, Marco Vecchiato, Massimiliano Vardè, Mauro Mazzola, François Yves Burgay, Federica Bruschi, Clara Jule Marie Hoppe, Allison Bailey, Andrea Gambaro, Carlo Barbante, Andrea Spolaor
Abstract. Arctic Amplification (AA) is leading to significant glacier ice melting, rapid sea ice decline, and alterations in atmospheric and geochemical processes in the Arctic regions, with consequences on the formation, transport, and chemical composition of aerosols and seasonal snowpack. Svalbard is particularly exposed to the AA, thus represents a relevant site in the Arctic to evaluate changes in local environmental processes contributing to the seasonal snow chemical composition. Sampling campaigns were conducted from 2018 to 2021 at the Gruvebadet Snow Research Site in Ny-Ålesund, in the North-West of the Svalbard Archipelago. During the investigated years, interannual variability of ionic and elemental impurities in surface snowpack has been associated to an alternation between relative warm years (2018–19, 2020–21), typical of the Arctic Amplification (AA) period, and relatively cold years (2019–20), more similar to the pre-AA conditions. Our results indicate that the concentration of impurities during the colder sampling season is strongly dependent on the production of sea spray related aerosol, likely deriving by a larger extension of sea ice, and drier, windy conditions. Our findings were therefore linked to the presence of sea ice in the Kongsfjorden in March 2020, and more generally around Spitsbergen, resulting from the exceptional occurrence of a strong and cold wintry stratospheric polar vortex and unusual AO index positive phase. By comparing the snow chemical composition of the 2019–20 season with 2018–19 and 2020–21, we present an overview of the possible impact of AA on the Svalbard snowpack, and the related change in the aerosol production process.
摘要。北极放大效应（AA）正在导致冰川融化、海冰迅速减少以及北极地区大气和地球化学过程的改变，从而对气溶胶和季节性积雪的形成、迁移和化学成分产生影响。斯瓦尔巴群岛尤其受到大气环流的影响，因此是北极地区评估当地环境过程变化对季节性积雪化学成分影响的相关地点。采样活动于 2018 年至 2021 年在斯瓦尔巴群岛西北部尼-奥勒松的 Gruvebadet 雪地研究基地进行。在所调查的年份中，地表积雪中离子和元素杂质的年际变化与相对温暖年份（2018-19 年、2020-21 年）和相对寒冷年份（2019-20 年）之间的交替有关，前者是典型的北极放大（AA）时期，后者则更类似于 AA 前的情况。我们的研究结果表明，较冷采样季节的杂质浓度在很大程度上取决于与海雾相关的气溶胶的产生，这可能是由于海冰的延伸范围更大，以及更干燥、多风的条件造成的。因此，我们的研究结果与 2020 年 3 月康斯峡湾海冰的存在有关，更广泛地说与斯匹次卑尔根周围海冰的存在有关，这是强冷风平流层极地涡旋和不寻常的 AO 指数正相异常出现的结果。通过比较2019-20年雪季与2018-19年和2020-21年雪季的雪化学成分，我们概述了AA对斯瓦尔巴雪堆可能产生的影响，以及气溶胶产生过程的相关变化。
{"title":"Impact of Arctic Amplification variability on the chemical composition of the snowpack in Svalbard","authors":"Azzurra Spagnesi, Elena Barbaro, Matteo Feltracco, Federico Scoto, Marco Vecchiato, Massimiliano Vardè, Mauro Mazzola, François Yves Burgay, Federica Bruschi, Clara Jule Marie Hoppe, Allison Bailey, Andrea Gambaro, Carlo Barbante, Andrea Spolaor","doi":"10.5194/egusphere-2024-1393","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1393","url":null,"abstract":"<strong>Abstract.</strong> Arctic Amplification (AA) is leading to significant glacier ice melting, rapid sea ice decline, and alterations in atmospheric and geochemical processes in the Arctic regions, with consequences on the formation, transport, and chemical composition of aerosols and seasonal snowpack. Svalbard is particularly exposed to the AA, thus represents a relevant site in the Arctic to evaluate changes in local environmental processes contributing to the seasonal snow chemical composition. Sampling campaigns were conducted from 2018 to 2021 at the Gruvebadet Snow Research Site in Ny-Ålesund, in the North-West of the Svalbard Archipelago. During the investigated years, interannual variability of ionic and elemental impurities in surface snowpack has been associated to an alternation between relative warm years (2018–19, 2020–21), typical of the Arctic Amplification (AA) period, and relatively cold years (2019–20), more similar to the pre-AA conditions. Our results indicate that the concentration of impurities during the colder sampling season is strongly dependent on the production of sea spray related aerosol, likely deriving by a larger extension of sea ice, and drier, windy conditions. Our findings were therefore linked to the presence of sea ice in the Kongsfjorden in March 2020, and more generally around Spitsbergen, resulting from the exceptional occurrence of a strong and cold wintry stratospheric polar vortex and unusual AO index positive phase. By comparing the snow chemical composition of the 2019–20 season with 2018–19 and 2020–21, we present an overview of the possible impact of AA on the Svalbard snowpack, and the related change in the aerosol production process.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"12 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-17DOI: 10.5194/egusphere-2024-1538
Ross J. Herbert, Alberto Sanchez-Marroquin, Daniel P. Grosvenor, Kirsty J. Pringle, Stephen R. Arnold, Benjamin J. Murray, Kenneth S. Carslaw
Abstract. Changes in the availability of a subset of aerosol known as ice-nucleating particles (INPs) can substantially alter cloud microphysical and radiative properties. Despite very large spatial and temporal variability in INP properties, many climate models do not currently represent the link between the global distribution of aerosols and INPs, and primary ice production in clouds. Here we use the UK Earth System Model to simulate the global distribution of dust and marine-sourced INPs over an annual cycle. The model captures the overall spatial and temporal distribution of measured INP concentrations, which is strongly influenced by the world’s major mineral dust source regions. A negative bias in simulated versus measured INP concentrations at higher freezing temperatures points to incorrectly defined INP properties or a missing source of INPs. We find that the ability of the model to reproduce measured INP concentrations is greatly improved by representing dust as a mixture of mineralogical and organic ice-nucleating components, as present in many soils. To improve the agreement further, we define an optimized hypothetical parameterization of dust INP activity (ns(T)) as a function of temperature with a logarithmic slope of -0.175 K−1, which is much shallower than existing parameterizations (e.g., -0.35 K−1 for the K-feldspar data of Harrison et al. (2019)). The results point to a globally important role for an organic component associated with mineral dust.
{"title":"Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK climate model","authors":"Ross J. Herbert, Alberto Sanchez-Marroquin, Daniel P. Grosvenor, Kirsty J. Pringle, Stephen R. Arnold, Benjamin J. Murray, Kenneth S. Carslaw","doi":"10.5194/egusphere-2024-1538","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1538","url":null,"abstract":"<strong>Abstract.</strong> Changes in the availability of a subset of aerosol known as ice-nucleating particles (INPs) can substantially alter cloud microphysical and radiative properties. Despite very large spatial and temporal variability in INP properties, many climate models do not currently represent the link between the global distribution of aerosols and INPs, and primary ice production in clouds. Here we use the UK Earth System Model to simulate the global distribution of dust and marine-sourced INPs over an annual cycle. The model captures the overall spatial and temporal distribution of measured INP concentrations, which is strongly influenced by the world’s major mineral dust source regions. A negative bias in simulated versus measured INP concentrations at higher freezing temperatures points to incorrectly defined INP properties or a missing source of INPs. We find that the ability of the model to reproduce measured INP concentrations is greatly improved by representing dust as a mixture of mineralogical and organic ice-nucleating components, as present in many soils. To improve the agreement further, we define an optimized hypothetical parameterization of dust INP activity (<em>n<sub>s</sub></em>(<em>T</em>)) as a function of temperature with a logarithmic slope of -0.175 K<sup>−1</sup>, which is much shallower than existing parameterizations (e.g., -0.35 K<sup>−1</sup> for the K-feldspar data of Harrison et al. (2019)). The results point to a globally important role for an organic component associated with mineral dust.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"21 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-14DOI: 10.5194/egusphere-2024-1443
Christine Borchers, Jackson Seymore, Martanda Gautam, Konstantin Dörholt, Yannik Müller, Andreas Arndt, Laura Gömmer, Florian Ungeheuer, Miklós Szakáll, Stephan Borrmann, Alexander Theis, Alexander Lucas Vogel, Thorsten Hoffmann
Abstract. Riming is an important growth process of graupel and hailstones in mixed-phase zones of clouds, during which supercooled liquid droplets freeze on the surface of ice particles by contact. Compounds dissolved in the supercooled cloud droplets can remain in the ice or be released to the gas phase during freezing, which might play an important role in the vertical redistribution of these compounds in the atmosphere by convective cloud processes. This is important for estimating the availability of these compounds in the upper troposphere, where organic matter can promote new particle formation and growth. The amount of organics remaining in the ice phase can be described by the retention coefficient. Experiments were performed in the Mainz vertical wind tunnel under dry and wet growth conditions (temperature from -12 to -3 °C and a liquid water contents (LWC) of 0.9 ± 0.2 g m-3 and 2.2 ± 0.2 g m-3) as well as different pH values (4 and 5.6) to obtain the retention coefficients of α-pinene oxidation products and nitro-aromatic compounds. For cis-pinic acid, cis-pinonic acid, and (-)-pinanediol mean retention coefficients of 0.96 ± 0.07, 0.92 ± 0.11and 0.98 ± 0.08 were obtained. 4-Nitrophenol, 4-nitrocatechol, 2‑nitrobenzoic acid, and 2‑nitrophenol showed mean retention coefficients of 1.01 ± 0.07, 1.01 ± 0.14, 0.99 ± 0.04 and 0.16 ± 0.10. Only the retention coefficient of 2-nitrophenol showed a dependence on temperature, growth regime, and pH. This is in accordance with previous studies which showed a dependence between the dimensionless effective Henry's law constant H* and the retention coefficient for inorganic and small organic molecules. Our results reveal that this correlation can also be applied to more complex organic molecules, and that retention under these conditions is negligible for molecules with H* below 103, while unity retention can be expected for compounds with H* above 108.
{"title":"Retention of α-pinene oxidation products and nitro-aromatic compounds during riming","authors":"Christine Borchers, Jackson Seymore, Martanda Gautam, Konstantin Dörholt, Yannik Müller, Andreas Arndt, Laura Gömmer, Florian Ungeheuer, Miklós Szakáll, Stephan Borrmann, Alexander Theis, Alexander Lucas Vogel, Thorsten Hoffmann","doi":"10.5194/egusphere-2024-1443","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1443","url":null,"abstract":"<strong>Abstract.</strong> Riming is an important growth process of graupel and hailstones in mixed-phase zones of clouds, during which supercooled liquid droplets freeze on the surface of ice particles by contact. Compounds dissolved in the supercooled cloud droplets can remain in the ice or be released to the gas phase during freezing, which might play an important role in the vertical redistribution of these compounds in the atmosphere by convective cloud processes. This is important for estimating the availability of these compounds in the upper troposphere, where organic matter can promote new particle formation and growth. The amount of organics remaining in the ice phase can be described by the retention coefficient. Experiments were performed in the Mainz vertical wind tunnel under dry and wet growth conditions (temperature from -12 to -3 °C and a liquid water contents (LWC) of 0.9 ± 0.2 g m<sup>-3</sup> and 2.2 ± 0.2 g m<sup>-3</sup>) as well as different pH values (4 and 5.6) to obtain the retention coefficients of α-pinene oxidation products and nitro-aromatic compounds. For cis-pinic acid, cis-pinonic acid, and (-)-pinanediol mean retention coefficients of 0.96 ± 0.07, 0.92 ± 0.11and 0.98 ± 0.08 were obtained. 4-Nitrophenol, 4-nitrocatechol, 2‑nitrobenzoic acid, and 2‑nitrophenol showed mean retention coefficients of 1.01 ± 0.07, 1.01 ± 0.14, 0.99 ± 0.04 and 0.16 ± 0.10. Only the retention coefficient of 2-nitrophenol showed a dependence on temperature, growth regime, and pH. This is in accordance with previous studies which showed a dependence between the dimensionless effective Henry's law constant <em>H</em>* and the retention coefficient for inorganic and small organic molecules. Our results reveal that this correlation can also be applied to more complex organic molecules, and that retention under these conditions is negligible for molecules with <em>H</em>* below 10<sup>3</sup>, while unity retention can be expected for compounds with <em>H</em>* above 10<sup>8</sup>.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"13 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141320020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Satellite-based column-averaged dry air CO2 mole fraction (XCO2) retrievals are frequently used to improve the estimates of terrestrial net carbon exchanges (NEE). The Orbiting Carbon Observatory 3 (OCO-3) satellite, launched in May 2019, was designed to address important questions about the distribution of carbon fluxes on Earth, but its role in estimating global terrestrial NEE remains unclear. Here, using the Global Carbon Assimilation System, version 2, we investigate the impact of OCO-3 XCO2 on the estimation of global NEE by assimilating the OCO-3 XCO2 retrievals alone and in combination with the OCO-2 XCO2 retrievals. The results show that when only the OCO-3 XCO2 is assimilated (Exp_OCO3), the estimated global land sink is significantly lower than that from the OCO-2 experiment (Exp_OCO2). The estimate from the joint assimilation of OCO-3 and OCO-2 (Exp_OCO3&2) is comparable on a global scale to that of Exp_OCO2. However, there are significant regional differences. Compared to the observed global annual CO2 growth rate, Exp_OCO3 has the largest bias, and Exp_OCO3&2 shows the best performance. Furthermore, validation with independent CO2 observations shows that the biases of the Exp_OCO3 are significantly larger than those of Exp_OCO2 and Exp_OCO3&2 at mid and high latitudes, probably due to the fact that OCO-3 only has observations from 52° S to 52° N. Our study indicates that assimilating OCO-3 XCO2 retrievals alone leads to an underestimation of land sinks at high latitudes, and that a joint assimilation of OCO-2 and OCO-3 XCO2 retrievals is required for a better estimation of global terrestrial NEE.
{"title":"The role of OCO-3 XCO2 retrievals in estimating global terrestrial net ecosystem exchanges","authors":"Xingyu Wang, Fei Jiang, Hengmao Wang, Zhengqi Zhang, Mousong Wu, Jun Wang, Wei He, Weimin Ju, Jingming Chen","doi":"10.5194/egusphere-2024-1568","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1568","url":null,"abstract":"<strong>Abstract.</strong> Satellite-based column-averaged dry air CO<sub>2</sub> mole fraction (XCO<sub>2</sub>) retrievals are frequently used to improve the estimates of terrestrial net carbon exchanges (NEE). The Orbiting Carbon Observatory 3 (OCO-3) satellite, launched in May 2019, was designed to address important questions about the distribution of carbon fluxes on Earth, but its role in estimating global terrestrial NEE remains unclear. Here, using the Global Carbon Assimilation System, version 2, we investigate the impact of OCO-3 XCO<sub>2</sub> on the estimation of global NEE by assimilating the OCO-3 XCO<sub>2</sub> retrievals alone and in combination with the OCO-2 XCO<sub>2</sub> retrievals. The results show that when only the OCO-3 XCO<sub>2</sub> is assimilated (Exp_OCO3), the estimated global land sink is significantly lower than that from the OCO-2 experiment (Exp_OCO2). The estimate from the joint assimilation of OCO-3 and OCO-2 (Exp_OCO3&2) is comparable on a global scale to that of Exp_OCO2. However, there are significant regional differences. Compared to the observed global annual CO<sub>2</sub> growth rate, Exp_OCO3 has the largest bias, and Exp_OCO3&2 shows the best performance. Furthermore, validation with independent CO<sub>2</sub> observations shows that the biases of the Exp_OCO3 are significantly larger than those of Exp_OCO2 and Exp_OCO3&2 at mid and high latitudes, probably due to the fact that OCO-3 only has observations from 52° S to 52° N. Our study indicates that assimilating OCO-3 XCO<sub>2</sub> retrievals alone leads to an underestimation of land sinks at high latitudes, and that a joint assimilation of OCO-2 and OCO-3 XCO<sub>2</sub> retrievals is required for a better estimation of global terrestrial NEE.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"43 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-14DOI: 10.5194/acp-24-6911-2024
Senyi Kong, Zheng Wang, Lei Bi
Abstract. Mineral dust particles are nonspherical and inhomogeneous; however, they are often simplified as homogeneous spherical particles for retrieving the refractive indices from laboratory measurements of scattering and absorption coefficients. The retrieved refractive indices are then employed for computing the optical properties of spherical or nonspherical dust model particles with downstream applications. This study aims to theoretically investigate uncertainties involved in the aforementioned rationale based on numerical simulations and focuses on a wavelength range of 355–1064 nm. Initially, the optical properties of nonspherical and inhomogeneous dust aerosols are computed as baseline cases. Subsequently, the scattering and absorption coefficients of homogeneous spheres and super-spheroids are computed at various refractive indices and compared with those of inhomogeneous dust aerosols to determine the dust refractive index. To mimic the real laboratory measurement, the size distribution of the baseline case is assumed to be unknown and determined through a process akin to using optical particle counters for sizing. The resulting size distribution differs from the original one of the baseline cases. The impact of discrepancies in size distributions on retrieving the dust refractive index is also investigated. Our findings reveal that these discrepancies affect scattering and absorption coefficients, presenting challenges in accurately determining the refractive index, particularly for the real parts. Additionally, the retrieved refractive indices are noted to vary with particle size primarily due to differences in size distribution, with imaginary parts decreasing as the particle size increases. A comparison between sphere models and super-spheroid models shows that the former tend to underestimate the imaginary parts, leading to an overestimation of single-scattering albedo. This study underscores the importance of employing consistent nonspherical models for both refractive index retrieval and subsequent optical simulation in downstream applications. Nevertheless, the impact of refractive index uncertainties on the asymmetry factor and phase matrix is found to be minimal, with particle shape playing a more significant role than differences in the imaginary parts of the dust refractive index.
{"title":"Uncertainties in laboratory-measured shortwave refractive indices of mineral dust aerosols and derived optical properties: a theoretical assessment","authors":"Senyi Kong, Zheng Wang, Lei Bi","doi":"10.5194/acp-24-6911-2024","DOIUrl":"https://doi.org/10.5194/acp-24-6911-2024","url":null,"abstract":"Abstract. Mineral dust particles are nonspherical and inhomogeneous; however, they are often simplified as homogeneous spherical particles for retrieving the refractive indices from laboratory measurements of scattering and absorption coefficients. The retrieved refractive indices are then employed for computing the optical properties of spherical or nonspherical dust model particles with downstream applications. This study aims to theoretically investigate uncertainties involved in the aforementioned rationale based on numerical simulations and focuses on a wavelength range of 355–1064 nm. Initially, the optical properties of nonspherical and inhomogeneous dust aerosols are computed as baseline cases. Subsequently, the scattering and absorption coefficients of homogeneous spheres and super-spheroids are computed at various refractive indices and compared with those of inhomogeneous dust aerosols to determine the dust refractive index. To mimic the real laboratory measurement, the size distribution of the baseline case is assumed to be unknown and determined through a process akin to using optical particle counters for sizing. The resulting size distribution differs from the original one of the baseline cases. The impact of discrepancies in size distributions on retrieving the dust refractive index is also investigated. Our findings reveal that these discrepancies affect scattering and absorption coefficients, presenting challenges in accurately determining the refractive index, particularly for the real parts. Additionally, the retrieved refractive indices are noted to vary with particle size primarily due to differences in size distribution, with imaginary parts decreasing as the particle size increases. A comparison between sphere models and super-spheroid models shows that the former tend to underestimate the imaginary parts, leading to an overestimation of single-scattering albedo. This study underscores the importance of employing consistent nonspherical models for both refractive index retrieval and subsequent optical simulation in downstream applications. Nevertheless, the impact of refractive index uncertainties on the asymmetry factor and phase matrix is found to be minimal, with particle shape playing a more significant role than differences in the imaginary parts of the dust refractive index.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"3 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-06-14DOI: 10.5194/acp-24-6883-2024
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert O. Green, Xavier Querol, Carlos Pérez García-Pando
Abstract. Characterising the physico-chemical properties of dust-emitting sediments in arid regions is fundamental to understanding the effects of dust on climate and ecosystems. However, knowledge regarding high-latitude dust (HLD) remains limited. This study focuses on analysing the particle size distribution (PSD), mineralogy, cohesion, iron (Fe) mode of occurrence, and visible–near infrared (VNIR) reflectance spectra of dust-emitting sediments from dust hotspots in Iceland (HLD region). Extensive analysis was conducted on samples of top sediments, sediments, and aeolian ripples collected from seven dust sources, with particular emphasis on the Jökulsá basin, encompassing the desert of Dyngjunsandur. Both fully and minimally dispersed PSDs and their respective mass median particle diameters revealed remarkable similarities (56 ± 69 and 55 ± 62 µm, respectively). Mineralogical analyses indicated the prevalence of amorphous phases (68 ± 26 %), feldspars (17 ± 13 %), and pyroxenes (9.3 ± 7.2 %), consistent with thorough analyses of VNIR reflectance spectra. The Fe content reached 9.5 ± 0.40 wt %, predominantly within silicate structures (80 ± 6.3 %), complemented by magnetite (16 ± 5.5 %), hematite/goethite (4.5 ± 2.7 %), and readily exchangeable Fe ions or Fe nano-oxides (1.6 ± 0.63 %). Icelandic top sediments exhibited coarser PSDs compared to the high dust-emitting crusts from mid-latitude arid regions, distinctive mineralogy, and a 3-fold bulk Fe content, with a significant presence of magnetite. The congruence between fully and minimally dispersed PSDs underscores reduced particle aggregation and cohesion of Icelandic top sediments, suggesting that aerodynamic entrainment of dust could also play a role upon emission in this region, alongside saltation bombardment. The extensive analysis in Dyngjusandur enabled the development of a conceptual model to encapsulate Iceland's rapidly evolving high dust-emitting environments.
{"title":"Probing Iceland's dust-emitting sediments: particle size distribution, mineralogy, cohesion, Fe mode of occurrence, and reflectance spectra signatures","authors":"Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert O. Green, Xavier Querol, Carlos Pérez García-Pando","doi":"10.5194/acp-24-6883-2024","DOIUrl":"https://doi.org/10.5194/acp-24-6883-2024","url":null,"abstract":"Abstract. Characterising the physico-chemical properties of dust-emitting sediments in arid regions is fundamental to understanding the effects of dust on climate and ecosystems. However, knowledge regarding high-latitude dust (HLD) remains limited. This study focuses on analysing the particle size distribution (PSD), mineralogy, cohesion, iron (Fe) mode of occurrence, and visible–near infrared (VNIR) reflectance spectra of dust-emitting sediments from dust hotspots in Iceland (HLD region). Extensive analysis was conducted on samples of top sediments, sediments, and aeolian ripples collected from seven dust sources, with particular emphasis on the Jökulsá basin, encompassing the desert of Dyngjunsandur. Both fully and minimally dispersed PSDs and their respective mass median particle diameters revealed remarkable similarities (56 ± 69 and 55 ± 62 µm, respectively). Mineralogical analyses indicated the prevalence of amorphous phases (68 ± 26 %), feldspars (17 ± 13 %), and pyroxenes (9.3 ± 7.2 %), consistent with thorough analyses of VNIR reflectance spectra. The Fe content reached 9.5 ± 0.40 wt %, predominantly within silicate structures (80 ± 6.3 %), complemented by magnetite (16 ± 5.5 %), hematite/goethite (4.5 ± 2.7 %), and readily exchangeable Fe ions or Fe nano-oxides (1.6 ± 0.63 %). Icelandic top sediments exhibited coarser PSDs compared to the high dust-emitting crusts from mid-latitude arid regions, distinctive mineralogy, and a 3-fold bulk Fe content, with a significant presence of magnetite. The congruence between fully and minimally dispersed PSDs underscores reduced particle aggregation and cohesion of Icelandic top sediments, suggesting that aerodynamic entrainment of dust could also play a role upon emission in this region, alongside saltation bombardment. The extensive analysis in Dyngjusandur enabled the development of a conceptual model to encapsulate Iceland's rapidly evolving high dust-emitting environments.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"43 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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