Because of the fractal aggregated structure of black carbon (BC), black carbon refractive index measurements are difficult. There are substantial differences among the over 40 existing measurement schemes and no two schemes are the same. Three typical BC refractive index schemes are chosen to explore the difference in black carbon optical properties and the consequences of the radiative effect. Two schemes are widely used in climate models, and the third is from a newer measurement in 2016. It is shown that black carbon optical properties are sensitive to different refractive indices. The relative differences in extinction coefficient and single scattering albedo can be over 100%. In addition, by using Maxwell–Garnett and Bruggeman mixing rules, it has been found that the effect of internal mixing on aerosol optical properties depends strongly on the choice of refractive index. Using a one‐dimensional radiative transfer model under clear‐sky conditions, we demonstrate that the choice of black carbon refractive index influences the inferred radiative effect. Using the more recent (2016) scheme for pure black carbon can increase the top‐of‐atmosphere radiative effect by 20% relative to the currently widely used lowest‐absorbing scheme. For internally mixed aerosol, the sign of the radiative effect can change depending on which refractive index is used.
{"title":"Accounting for black carbon refractive index in atmospheric radiation","authors":"Jiangnan Li, Ruth Digby, Knut von Salzen","doi":"10.1002/qj.4842","DOIUrl":"https://doi.org/10.1002/qj.4842","url":null,"abstract":"Because of the fractal aggregated structure of black carbon (BC), black carbon refractive index measurements are difficult. There are substantial differences among the over 40 existing measurement schemes and no two schemes are the same. Three typical BC refractive index schemes are chosen to explore the difference in black carbon optical properties and the consequences of the radiative effect. Two schemes are widely used in climate models, and the third is from a newer measurement in 2016. It is shown that black carbon optical properties are sensitive to different refractive indices. The relative differences in extinction coefficient and single scattering albedo can be over 100%. In addition, by using Maxwell–Garnett and Bruggeman mixing rules, it has been found that the effect of internal mixing on aerosol optical properties depends strongly on the choice of refractive index. Using a one‐dimensional radiative transfer model under clear‐sky conditions, we demonstrate that the choice of black carbon refractive index influences the inferred radiative effect. Using the more recent (2016) scheme for pure black carbon can increase the top‐of‐atmosphere radiative effect by 20% relative to the currently widely used lowest‐absorbing scheme. For internally mixed aerosol, the sign of the radiative effect can change depending on which refractive index is used.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"13 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A linear theory of the trapped mountain waves that develop in a turbulent boundary layer is presented. The theory uses a mixing‐length turbulence model based on Monin–Obukhov similarity theory. First, the backward reflection of a stationary gravity wave propagating toward the ground is examined. Three parameters are investigated systematically: the Monin–Obukhov length , the roughness length , and the limit value of the mixing length aloft the “inner” layer. The reflection coefficient appears to depend strongly on the Richardson number aloft the inner layer (, with the von Kármán constant), with the reflection decreasing when the stability increases. The influence of the roughness and mixing lengths on the reflection is explained in terms of the depth of a “pseudo”‐critical level located below the surface, with the reflection decreasing when the depth of the “pseudo”‐critical level decreases. The preferential modes of oscillations occurring in the presence of mountain forcing are then analysed, with the decay rate of the trapped waves downstream increasing when the reflection decreases. At a certain point nevertheless, when the absorption is large but the boundary‐layer depth deep enough, trapped modes appear that interact little with the surface.
{"title":"Mountain waves developing inside and aloft stably stratified turbulent boundary layers","authors":"Lucile Pauget, Francois Lott, Christophe Millet","doi":"10.1002/qj.4832","DOIUrl":"https://doi.org/10.1002/qj.4832","url":null,"abstract":"A linear theory of the trapped mountain waves that develop in a turbulent boundary layer is presented. The theory uses a mixing‐length turbulence model based on Monin–Obukhov similarity theory. First, the backward reflection of a stationary gravity wave propagating toward the ground is examined. Three parameters are investigated systematically: the Monin–Obukhov length , the roughness length , and the limit value of the mixing length aloft the “inner” layer. The reflection coefficient appears to depend strongly on the Richardson number aloft the inner layer (, with the von Kármán constant), with the reflection decreasing when the stability increases. The influence of the roughness and mixing lengths on the reflection is explained in terms of the depth of a “pseudo”‐critical level located below the surface, with the reflection decreasing when the depth of the “pseudo”‐critical level decreases. The preferential modes of oscillations occurring in the presence of mountain forcing are then analysed, with the decay rate of the trapped waves downstream increasing when the reflection decreases. At a certain point nevertheless, when the absorption is large but the boundary‐layer depth deep enough, trapped modes appear that interact little with the surface.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"9 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel González‐Fernández, Roberto Román, Juan Carlos Antuña‐Sánchez, Victoria E. Cachorro, Gustavo Copes, Sara Herrero‐Anta, Celia Herrero del Barrio, África Barreto, Ramiro González, Ramón Ramos, Patricia Martín, David Mateos, Carlos Toledano, Abel Calle, Ángel de Frutos
We present a new model based on a convolutional neural network (CNN) to predict daytime cloud cover (CC) from sky images captured by all‐sky cameras, which is called CNN‐CC. A total of 49,016 daytime sky images, recorded at different Spanish locations (Valladolid, La Palma, and Izaña) from two different all‐sky camera types, are manually classified into different CC (oktas) values by trained researchers. Subsequently, the images are randomly split into a training set and a test set to validate the model. The CC values predicted by the CNN‐CC model are compared with the observations made by trained people on the test set, which serve as reference. The predicted CC values closely match the reference values within 1 oktas in 99% of the cloud‐free and overcast cases. Moreover, this percentage is above 93% for the rest of partially cloudy cases. The mean bias error (MBE) and standard deviation (SD) of the differences between the predicted and reference CC values are calculated, resulting in oktas and oktas. The MBE and SD are also represented for different intervals of measured aerosol optical depth and Ångström exponent values, revealing that the performance of the CNN‐CC model does not depend on aerosol load or size. Once the model is validated, the CC obtained from a set of images captured every 5 min, from January 2018 to March 2022, at the Antarctic station of Marambio (Argentina) is compared against direct field observations of CC (not from images) taken at this location, which is not used in the training process. As a result, the model slightly underestimates the observations with an MBE of 0.3 oktas. The retrieved data are analyzed in detail. The monthly and annual CC values are calculated. Overcast conditions are the most frequent, accounting for 46.5% of all observations throughout the year, rising to 64.5% in January. The annual mean CC value at this location is 5.5 oktas, with a standard deviation of approximately 3.1 oktas. A similar analysis is conducted, separating data by hours, but no significant diurnal cycles are observed except for some isolated months.
我们提出了一种基于卷积神经网络（CNN）的新模型，用于预测全天空照相机拍摄的天空图像中的日间云量（CC），该模型被称为 CNN-CC。训练有素的研究人员将在西班牙不同地点（巴利亚多利德、拉帕尔马和伊萨尼亚）用两种不同类型的全天空照相机拍摄的 49,016 幅白天天空图像手动分类为不同的 CC（oktas）值。随后，这些图像被随机分成训练集和测试集，以验证模型。CNN-CC 模型预测的 CC 值与经过培训的人员对测试集（作为参考）的观察结果进行比较。在 99% 的无云和阴天情况下，预测的 CC 值与参考值的吻合度在 1 oktas 以内。此外，在其他部分多云的情况下，这一比例也在 93% 以上。计算预测 CC 值与参考 CC 值之间差异的平均偏差误差 (MBE) 和标准偏差 (SD)，得出 oktas 和 oktas。平均偏差误差（MBE）和标准偏差（SD）还表示了气溶胶光学深度测量值和Ångström 指数值的不同区间，揭示了 CNN-CC 模型的性能与气溶胶负荷或大小无关。模型得到验证后，将 2018 年 1 月至 2022 年 3 月期间在南极马兰比奥站（阿根廷）每 5 分钟拍摄的一组图像中获得的 CC 与在该地点拍摄的直接实地 CC 观测数据（非图像）进行比较，后者未用于训练过程。结果，模型略微低估了观测数据，MBE 为 0.3 oktas。对检索到的数据进行了详细分析。计算了每月和每年的 CC 值。阴天情况最常见，占全年观测值的 46.5%，1 月份上升到 64.5%。该地点的 CC 年平均值为 5.5 oktas，标准偏差约为 3.1 oktas。按小时数对数据进行了类似的分析，但除个别月份外，没有观察到明显的昼夜周期。
{"title":"A neural network to retrieve cloud cover from all‐sky cameras: A case of study over Antarctica","authors":"Daniel González‐Fernández, Roberto Román, Juan Carlos Antuña‐Sánchez, Victoria E. Cachorro, Gustavo Copes, Sara Herrero‐Anta, Celia Herrero del Barrio, África Barreto, Ramiro González, Ramón Ramos, Patricia Martín, David Mateos, Carlos Toledano, Abel Calle, Ángel de Frutos","doi":"10.1002/qj.4834","DOIUrl":"https://doi.org/10.1002/qj.4834","url":null,"abstract":"We present a new model based on a convolutional neural network (CNN) to predict daytime cloud cover (CC) from sky images captured by all‐sky cameras, which is called CNN‐CC. A total of 49,016 daytime sky images, recorded at different Spanish locations (Valladolid, La Palma, and Izaña) from two different all‐sky camera types, are manually classified into different CC (oktas) values by trained researchers. Subsequently, the images are randomly split into a training set and a test set to validate the model. The CC values predicted by the CNN‐CC model are compared with the observations made by trained people on the test set, which serve as reference. The predicted CC values closely match the reference values within 1 oktas in 99% of the cloud‐free and overcast cases. Moreover, this percentage is above 93% for the rest of partially cloudy cases. The mean bias error (MBE) and standard deviation (SD) of the differences between the predicted and reference CC values are calculated, resulting in oktas and oktas. The MBE and SD are also represented for different intervals of measured aerosol optical depth and Ångström exponent values, revealing that the performance of the CNN‐CC model does not depend on aerosol load or size. Once the model is validated, the CC obtained from a set of images captured every 5 min, from January 2018 to March 2022, at the Antarctic station of Marambio (Argentina) is compared against direct field observations of CC (not from images) taken at this location, which is not used in the training process. As a result, the model slightly underestimates the observations with an MBE of 0.3 oktas. The retrieved data are analyzed in detail. The monthly and annual CC values are calculated. Overcast conditions are the most frequent, accounting for 46.5% of all observations throughout the year, rising to 64.5% in January. The annual mean CC value at this location is 5.5 oktas, with a standard deviation of approximately 3.1 oktas. A similar analysis is conducted, separating data by hours, but no significant diurnal cycles are observed except for some isolated months.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"23 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tropical precipitation has been found to be related to column relative humidity by a simple relationship known as the moisture–precipitation relationship . Based on one decade of daily ERA5 reanalysis data, we test whether is able to reproduce the tropical land–ocean precipitation contrast measured by , the ratio between mean precipitation over land and ocean. We find that captures the mean seasonal cycle of as long as we account for the fact that is distinct over land and ocean, and that it varies seasonally. Typical values of above 0.86 imply that precipitation is enhanced over land, relative to the ocean. We therefore investigate next whether this enhancement is due to the differences in and/or in the humidity distribution between land and ocean. We show that, rather than enhancing precipitation, the presence of land modifies in such a way that precipitation over land is disfavored compared to over ocean. Precipitation enhancement over land is instead explained by the modified terrestrial humidity distribution that features a more pronounced tail towards high values compared to the one over ocean. All results rest on an accurate construction of from the underlying data. Simple fit models such as an exponential function that were proposed by previous studies are unable to capture the seasonal cycle of and fail to explain land–ocean differences in precipitation.
{"title":"Precipitation enhancement over tropical land through the lens of the moisture–precipitation relationship","authors":"Luca Schmidt, Cathy Hohenegger","doi":"10.1002/qj.4838","DOIUrl":"https://doi.org/10.1002/qj.4838","url":null,"abstract":"Tropical precipitation has been found to be related to column relative humidity by a simple relationship known as the moisture–precipitation relationship . Based on one decade of daily ERA5 reanalysis data, we test whether is able to reproduce the tropical land–ocean precipitation contrast measured by , the ratio between mean precipitation over land and ocean. We find that captures the mean seasonal cycle of as long as we account for the fact that is distinct over land and ocean, and that it varies seasonally. Typical values of above 0.86 imply that precipitation is enhanced over land, relative to the ocean. We therefore investigate next whether this enhancement is due to the differences in and/or in the humidity distribution between land and ocean. We show that, rather than enhancing precipitation, the presence of land modifies in such a way that precipitation over land is disfavored compared to over ocean. Precipitation enhancement over land is instead explained by the modified terrestrial humidity distribution that features a more pronounced tail towards high values compared to the one over ocean. All results rest on an accurate construction of from the underlying data. Simple fit models such as an exponential function that were proposed by previous studies are unable to capture the seasonal cycle of and fail to explain land–ocean differences in precipitation.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"46 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erik W. Kolstad, Douglas J. Parker, David A. MacLeod, Caroline M. Wainwright, Linda C. Hirons
The East African “short rains” from October–December (OND) are crucial for the region's cultural and agricultural landscape. Traditional climate studies have often treated these rains as a single mode, representing the average rainfall across the region. This approach, however, fails to capture the complex geographical variations in seasonal rainfall. In our study, we analyse 4200 reforecasts from a seasonal prediction system spanning 1981–2022, identifying distinct clusters that represent different geographical patterns of the short rains. We explore the influence of tropical sea‐surface temperature patterns, upper‐level tropospheric flow, and low‐level moisture fluxes on these clusters. A key revelation of our research is the limited predictability of certain geographical rainfall structures based on large‐scale climatic drivers. This finding highlights a gap in current forecasting methodologies, emphasising the necessity for further research to understand and predict these intricate patterns. Our study illuminates the complexities of regional rainfall variability in East Africa, underlining the importance of continued investigation to improve climate resilience strategies in the region.
{"title":"Beyond the regional average: Drivers of geographical rainfall variability during East Africa's short rains","authors":"Erik W. Kolstad, Douglas J. Parker, David A. MacLeod, Caroline M. Wainwright, Linda C. Hirons","doi":"10.1002/qj.4829","DOIUrl":"https://doi.org/10.1002/qj.4829","url":null,"abstract":"The East African “short rains” from October–December (OND) are crucial for the region's cultural and agricultural landscape. Traditional climate studies have often treated these rains as a single mode, representing the average rainfall across the region. This approach, however, fails to capture the complex geographical variations in seasonal rainfall. In our study, we analyse 4200 reforecasts from a seasonal prediction system spanning 1981–2022, identifying distinct clusters that represent different geographical patterns of the short rains. We explore the influence of tropical sea‐surface temperature patterns, upper‐level tropospheric flow, and low‐level moisture fluxes on these clusters. A key revelation of our research is the limited predictability of certain geographical rainfall structures based on large‐scale climatic drivers. This finding highlights a gap in current forecasting methodologies, emphasising the necessity for further research to understand and predict these intricate patterns. Our study illuminates the complexities of regional rainfall variability in East Africa, underlining the importance of continued investigation to improve climate resilience strategies in the region.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"19 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alex Brown, Thomas M. Bendall, Ian Boutle, Thomas Melvin, Ben Shipway
The main components of an atmospheric model for numerical weather prediction are the “dynamical core,” which describes the resolved flow, and the “physical parametrisation,” which capture the effects of non‐fluid and non‐resolved fluid processes. Additionally, models used for air quality or climate applications may include a component that represents the evolution of chemicals and aerosols within the atmosphere. Though, traditionally, all these components use the same mesh with the same grid spacing, we present a formulation for the different components to use a series of nested meshes, with different horizontal grid spacings. This gives the model greater flexibility in the allocation of computational resources, so that resolution can be targeted to those parts that provide the greatest benefits in accuracy. The formulation presented here concerns the methods for mapping fields between meshes and is designed for the compatible finite‐element discretisation used by LFRic‐Atmosphere, the Met Office's next‐generation atmosphere model. Key properties of the formulation include the consistent and conservative transport of tracers on a mesh that is coarser than the dynamical core, and the handling of moisture to ensure mass conservation without generation of unphysical negative values. Having presented the formulation, it is then demonstrated through a series of idealised test cases that show the feasibility of this approach.
{"title":"Physics–dynamics–chemistry coupling across different meshes in LFRic‐Atmosphere: Formulation and idealised tests","authors":"Alex Brown, Thomas M. Bendall, Ian Boutle, Thomas Melvin, Ben Shipway","doi":"10.1002/qj.4836","DOIUrl":"https://doi.org/10.1002/qj.4836","url":null,"abstract":"The main components of an atmospheric model for numerical weather prediction are the “dynamical core,” which describes the resolved flow, and the “physical parametrisation,” which capture the effects of non‐fluid and non‐resolved fluid processes. Additionally, models used for air quality or climate applications may include a component that represents the evolution of chemicals and aerosols within the atmosphere. Though, traditionally, all these components use the same mesh with the same grid spacing, we present a formulation for the different components to use a series of nested meshes, with different horizontal grid spacings. This gives the model greater flexibility in the allocation of computational resources, so that resolution can be targeted to those parts that provide the greatest benefits in accuracy. The formulation presented here concerns the methods for mapping fields between meshes and is designed for the compatible finite‐element discretisation used by LFRic‐Atmosphere, the Met Office's next‐generation atmosphere model. Key properties of the formulation include the consistent and conservative transport of tracers on a mesh that is coarser than the dynamical core, and the handling of moisture to ensure mass conservation without generation of unphysical negative values. Having presented the formulation, it is then demonstrated through a series of idealised test cases that show the feasibility of this approach.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During the 2022 Asian summer monsoon, the climatological driest parts of Sindh and Balochistan provinces in southwestern Pakistan and the northern Arabian Sea (regions of climatological heat low, HLOW) experienced unprecedented precipitation (>500% of the normal) whereas precipitation was reduced from the Indo‐Gangetic Plain to the tropical western Pacific. Our working hypothesis is that the weakened large‐scale monsoon is a direct response to tropical sea‐surface temperature: wave responses that develop in response to changes in diabatic heating anomalies over the regional precipitation centers within the Asian monsoon intensify and transition HLOW into an anomalous moist low. To validate the hypothesis, process‐oriented diagnostics are applied to European Centre of Medium‐range Weather Forecasts Reanalysis v5 (ERA5), and numerical experiments are performed with a linear atmospheric general circulation model. Model solutions confirm that the weakened large‐scale monsoon, essentially a linear response, is determined by persistent warm sea‐surface temperature and enhanced precipitation anomalies over the equatorial and southeastern Indian Ocean–Maritime Continent, and Rossby waves emanating from there, and from continental India, deepen the HLOW. Concomitantly, as a Rossby wave response to negative precipitation anomalies over the northern Bay of Bengal and Indochina during June, and their poleward migration during July–August, positive height anomalies develop and intensify over northern India. The resultant horizontal pressure gradient between HLOW and northern India drives concentrated low‐level wind anomalies that are efficient in advecting the strongest climatological moisture gradient to precondition the lower troposphere during June, and in determining the unprecedented precipitation during July–August when the seasonal cycle prevails over HLOW. Model sensitivity to horizontal moisture advection confirms ERA5 diagnostics. Nearly identical tropical forcing and large‐scale weakened monsoon responses are observed during 2010 and 2020. In these years, diagnostics identify subtle changes in latitudinal position of negative precipitation anomalies over the Bay of Bengal and Indo‐Gangetic Plain that lead to lesser contribution by horizontal moisture advection, resulting in weaker positive precipitation anomalies over southwest Pakistan.
{"title":"Unprecedented monsoon precipitation over southwest Pakistan in 2022: Regional processes in moistening the climatological heat low","authors":"H. Annamalai","doi":"10.1002/qj.4821","DOIUrl":"https://doi.org/10.1002/qj.4821","url":null,"abstract":"During the 2022 Asian summer monsoon, the climatological driest parts of Sindh and Balochistan provinces in southwestern Pakistan and the northern Arabian Sea (regions of climatological heat low, H<jats:sub>LOW</jats:sub>) experienced unprecedented precipitation (>500% of the normal) whereas precipitation was reduced from the Indo‐Gangetic Plain to the tropical western Pacific. Our working hypothesis is that the weakened large‐scale monsoon is a direct response to tropical sea‐surface temperature: wave responses that develop in response to changes in diabatic heating anomalies over the regional precipitation centers within the Asian monsoon intensify and transition H<jats:sub>LOW</jats:sub> into an anomalous moist low. To validate the hypothesis, process‐oriented diagnostics are applied to European Centre of Medium‐range Weather Forecasts Reanalysis v5 (ERA5), and numerical experiments are performed with a linear atmospheric general circulation model. Model solutions confirm that the weakened large‐scale monsoon, essentially a linear response, is determined by persistent warm sea‐surface temperature and enhanced precipitation anomalies over the equatorial and southeastern Indian Ocean–Maritime Continent, and Rossby waves emanating from there, and from continental India, deepen the H<jats:sub>LOW</jats:sub>. Concomitantly, as a Rossby wave response to negative precipitation anomalies over the northern Bay of Bengal and Indochina during June, and their poleward migration during July–August, positive height anomalies develop and intensify over northern India. The resultant horizontal pressure gradient between H<jats:sub>LOW</jats:sub> and northern India drives concentrated low‐level wind anomalies that are efficient in advecting the strongest climatological moisture gradient to precondition the lower troposphere during June, and in determining the unprecedented precipitation during July–August when the seasonal cycle prevails over H<jats:sub>LOW</jats:sub>. Model sensitivity to horizontal moisture advection confirms ERA5 diagnostics. Nearly identical tropical forcing and large‐scale weakened monsoon responses are observed during 2010 and 2020. In these years, diagnostics identify subtle changes in latitudinal position of negative precipitation anomalies over the Bay of Bengal and Indo‐Gangetic Plain that lead to lesser contribution by horizontal moisture advection, resulting in weaker positive precipitation anomalies over southwest Pakistan.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"36 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article presents an analytical model for the diurnal cycle of slope‐normal profiles of potential temperature and wind speed characterizing thermally driven slope winds, generated by a daily‐periodic surface energy budget. The model extends the solution proposed by Zardi and Serafin, originally formulated for a pure sinusoidal surface forcing temperature. To account for the asymmetric features characterizing the daytime and nighttime phases, a full Fourier series expansion is derived, the coefficients and phases of which are prescribed from the surface energy budget driven by the daily‐periodic radiation model described in Part 1 of the present work. The model is applicable for any slope angle () and orientation, at any latitude and elevation (up to 2500 m), and for all seasons. Despite some inherent limitations, the most remarkable being the absence of moist processes and latent heat fluxes, the model captures most key features of daily‐periodic slope wind systems, in particular the asymmetry between daytime and nighttime phases. Moreover, it allows exploration of the sensitivity of these flows to the various factors concurring in their development, and offers a basis for more realistic analytical solutions for slope winds.
{"title":"An analytical model for daily‐periodic slope winds. Part 2: Solutions","authors":"Mattia Marchio, Sofia Farina, Dino Zardi","doi":"10.1002/qj.4787","DOIUrl":"https://doi.org/10.1002/qj.4787","url":null,"abstract":"This article presents an analytical model for the diurnal cycle of slope‐normal profiles of potential temperature and wind speed characterizing thermally driven slope winds, generated by a daily‐periodic surface energy budget. The model extends the solution proposed by Zardi and Serafin, originally formulated for a pure sinusoidal surface forcing temperature. To account for the asymmetric features characterizing the daytime and nighttime phases, a full Fourier series expansion is derived, the coefficients and phases of which are prescribed from the surface energy budget driven by the daily‐periodic radiation model described in Part 1 of the present work. The model is applicable for any slope angle () and orientation, at any latitude and elevation (up to 2500 m), and for all seasons. Despite some inherent limitations, the most remarkable being the absence of moist processes and latent heat fluxes, the model captures most key features of daily‐periodic slope wind systems, in particular the asymmetry between daytime and nighttime phases. Moreover, it allows exploration of the sensitivity of these flows to the various factors concurring in their development, and offers a basis for more realistic analytical solutions for slope winds.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"160 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Polar lows exhibit features with very sharp weather contrasts. In weather forecasting, a small misplacement of areas with hazardously high wind speeds can have fatal impacts for people living in polar regions. Therefore, a novel application of spatial verification methods for objective metrics of size, shape, and location of areas with hazardous weather is tested. To separate the effect of errors in polar low location and direction of motion from errors relative to the polar low centre, surface wind fields from the limited‐area weather forecasting model Applications of Research to Operations at Mesoscale‐Arctic and Copernicus Climate Change Service Arctic Regional Reanalysis are centred at the polar low centre and rotated according to the direction of background flow surrounding the polar low. Then the possibilities of the features‐based verification methods SAL (structure, amplitude, location) and MODE (Method for Object‐based Diagnostic Evaluation) are explored using a test case from October 2019. The study demonstrates that the methodology can provide valuable information about forecast performance. MODE is a flexible method with metrics that focus on characteristics of individual objects and can be adapted to questions at hand. For example, a measure of storm eye size was added. SAL, on the other hand, provides effective summary metrics for the full domain and proved particularly useful for evaluation of the overall distribution of wind speed. To evaluate the number of correctly or incorrectly identified areas with harsh weather rather than their details about their shape, contingency scores are more suitable. Applied to a larger dataset, this methodology can assess performance as a function of forecast length, as well as geographical area, and the type of polar low. The methodology can also be applied to other types of low‐pressure systems, such as extratropical cyclones.
{"title":"Developing a methodology for user‐oriented verification of polar low forecasts","authors":"Matilda Hallerstig, Morten Ødegaard Køltzow, Stephanie Mayer","doi":"10.1002/qj.4819","DOIUrl":"https://doi.org/10.1002/qj.4819","url":null,"abstract":"Polar lows exhibit features with very sharp weather contrasts. In weather forecasting, a small misplacement of areas with hazardously high wind speeds can have fatal impacts for people living in polar regions. Therefore, a novel application of spatial verification methods for objective metrics of size, shape, and location of areas with hazardous weather is tested. To separate the effect of errors in polar low location and direction of motion from errors relative to the polar low centre, surface wind fields from the limited‐area weather forecasting model Applications of Research to Operations at Mesoscale‐Arctic and Copernicus Climate Change Service Arctic Regional Reanalysis are centred at the polar low centre and rotated according to the direction of background flow surrounding the polar low. Then the possibilities of the features‐based verification methods SAL (structure, amplitude, location) and MODE (Method for Object‐based Diagnostic Evaluation) are explored using a test case from October 2019. The study demonstrates that the methodology can provide valuable information about forecast performance. MODE is a flexible method with metrics that focus on characteristics of individual objects and can be adapted to questions at hand. For example, a measure of storm eye size was added. SAL, on the other hand, provides effective summary metrics for the full domain and proved particularly useful for evaluation of the overall distribution of wind speed. To evaluate the number of correctly or incorrectly identified areas with harsh weather rather than their details about their shape, contingency scores are more suitable. Applied to a larger dataset, this methodology can assess performance as a function of forecast length, as well as geographical area, and the type of polar low. The methodology can also be applied to other types of low‐pressure systems, such as extratropical cyclones.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"23 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud microphysics fulfills a fundamental role in the formation and evolution of marine fog, but it is not fully understood. Numerous studies have addressed this by means of direct observations and modeling efforts. However, collision–coalescence of aerosols and fog droplets is a process often neglected. In this study we perform an analysis of the role of particle collections on the formation, development, and microphysical structure of marine fog. It was found that collisions open a path for aerosol activation by means of collisional activation. In addition, collisions contribute to the diffusional activation of fog particles by adding water mass to the growing aerosols, making them reach the required critical radius faster. Furthermore, collisions have a homogenizing effect on hygroscopicity, facilitating the activation of accumulation‐mode aerosols by increasing their diffusional growth.
{"title":"The role of collision and coalescence on the microphysics of marine fog","authors":"Camilo F. Rodriguez‐Geno, David H. Richter","doi":"10.1002/qj.4831","DOIUrl":"https://doi.org/10.1002/qj.4831","url":null,"abstract":"Cloud microphysics fulfills a fundamental role in the formation and evolution of marine fog, but it is not fully understood. Numerous studies have addressed this by means of direct observations and modeling efforts. However, collision–coalescence of aerosols and fog droplets is a process often neglected. In this study we perform an analysis of the role of particle collections on the formation, development, and microphysical structure of marine fog. It was found that collisions open a path for aerosol activation by means of collisional activation. In addition, collisions contribute to the diffusional activation of fog particles by adding water mass to the growing aerosols, making them reach the required critical radius faster. Furthermore, collisions have a homogenizing effect on hygroscopicity, facilitating the activation of accumulation‐mode aerosols by increasing their diffusional growth.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：