Abstract. Atmospheric boundary layers (ABLs) exhibit transient processes on various time scales that range from a few days down to seconds, with a scale separation of the large-scale forcing and the small-scale turbulent response. One of the standing challenges in modeling and simulation of ABLs is a physically based representation of complex multiscale boundary layer dynamics. In this study, an idealized time-dependent ABL, the so-called Ekman–Stokes boundary layer (ESBL), is considered as a simple model for the near-surface flow in the mid latitudes and polar regions. The ESBL is driven by a prescribed temporal modulation of the bulk–surface velocity difference. A stochastic one-dimensional turbulence (ODT) model is applied to the ESBL as standalone tool that aims to resolve all relevant scales of the flow along a representative vertical coordinate. It is demonstrated by comparison with reference data that ODT is able to capture relevant features of the time-dependent boundary layer flow. The model predicts a parametric enhancement of the bulk–surface coupling in the event of a boundary layer resonance when the flow is forced with the local Coriolis frequency. The latter reproduces leading order effects of the critical latitudes. The model results suggest that the bulk flow decouples from the surface for high forcing frequencies due to a relative increase in detached residual turbulence.
{"title":"Capturing features of turbulent Ekman–Stokes boundary layers with a stochastic modeling approach","authors":"M. Klein, H. Schmidt","doi":"10.5194/asr-20-55-2023","DOIUrl":"https://doi.org/10.5194/asr-20-55-2023","url":null,"abstract":"Abstract. Atmospheric boundary layers (ABLs) exhibit transient processes on various time scales that range from a few days down to seconds, with a scale separation of the large-scale forcing and the small-scale turbulent response.\u0000One of the standing challenges in modeling and simulation of ABLs is a physically based representation of complex multiscale boundary layer dynamics.\u0000In this study, an idealized time-dependent ABL, the so-called Ekman–Stokes boundary layer (ESBL), is considered as a simple model for the near-surface flow in the mid latitudes and polar regions.\u0000The ESBL is driven by a prescribed temporal modulation of the bulk–surface velocity difference.\u0000A stochastic one-dimensional turbulence (ODT) model is applied to the ESBL as standalone tool that aims to resolve all relevant scales of the flow along a representative vertical coordinate.\u0000It is demonstrated by comparison with reference data that ODT is able to capture relevant features of the time-dependent boundary layer flow.\u0000The model predicts a parametric enhancement of the bulk–surface coupling in the event of a boundary layer resonance when the flow is forced with the local Coriolis frequency.\u0000The latter reproduces leading order effects of the critical latitudes.\u0000The model results suggest that the bulk flow decouples from the surface for high forcing frequencies due to a relative increase in detached residual turbulence.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"101 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75285004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jouke H. S. de Baar, Irene Garcia‐Marti, G. van der Schrier
Abstract. High-resolution weather maps are fundamental components of early warning systems, since they enable the (near) real-time tracking of extreme weather events. In this context, crowd-sourced weather networks producing low-fidelity observations are often the only type of data available at local (e.g. neighborhood) scales. In this work, we demonstrate that we can provide such maps by combining high-fidelity official weather data with low-fidelity crowd-sourced weather data and high-resolution covariate information. Because the crowd-sourced data contains significant bias and noise, we develop an approach to include a bias budget and noise budget in the multi-fidelity Bayesian spatial data analysis. The weights of the different components of these bias and noise budgets are tuned to the data set. We apply this approach to 24 hours of weather data in the Netherlands, for a day that had a “code orange” (i.e. “be prepared for extreme weather with high risk of impact”) weather warning for heavy precipitation. From our analysis, we see a significant – qualitative and quantitative – synergy effect when introducing low-fidelity data and high-resolution covariate information.
{"title":"Spatial regression of multi-fidelity meteorological observations using a proxy-based measurement error model","authors":"Jouke H. S. de Baar, Irene Garcia‐Marti, G. van der Schrier","doi":"10.5194/asr-20-49-2023","DOIUrl":"https://doi.org/10.5194/asr-20-49-2023","url":null,"abstract":"Abstract. High-resolution weather maps are fundamental components of early warning systems, since they enable the (near) real-time tracking of extreme weather events. In this context, crowd-sourced weather networks producing low-fidelity observations are often the only type of data available at local (e.g. neighborhood) scales. In this work, we demonstrate that we can provide such maps by combining high-fidelity official weather data with low-fidelity crowd-sourced weather data and high-resolution covariate information. Because the crowd-sourced data contains significant bias and noise, we develop an approach to include a bias budget and noise budget in the multi-fidelity Bayesian spatial data analysis. The weights of the different components of these bias and noise budgets are tuned to the data set. We apply this approach to 24 hours of weather data in the Netherlands, for a day that had a “code orange” (i.e. “be prepared for extreme weather with high risk of impact”) weather warning for heavy precipitation. From our analysis, we see a significant – qualitative and quantitative – synergy effect when introducing low-fidelity data and high-resolution covariate information.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88532487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Lussana, Emma Baietti, Line Båserud, T. Nipen, I. Seierstad
Abstract. We present a comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national meteorological services, the latter used as reference values. The empirical distributions of the crowdsourced observations in the surroundings of reference stations are used to assess accuracy and precision of crowdsourced data. We found that reference values are typically within the distribution of the crowdsourced data. However, as the amount of precipitation increases, the spread of the crowdsourced distribution increases and the reference values are more and more frequently found towards the right tail of the distribution. These results indicate that accuracy and precision of crowdsourced data change as precipitation increases. We have studied the sensitivity of our results to the size of the neighbourhood chosen around the reference stations and we show that by aggregating the values over those neighbourhoods, crowdsourced data can be trusted in determining precipitation occurrence. We have assessed the variability of precipitation within small neighbourhoods (of radius 1, 3 and 5 km) and we provide estimates on the basis of the precipitation amounts. Our study quantifies the variability of hourly precipitation over small regions, of the size of the so-called “unresolved spatial scales” in limited area models, based on three years of data collected at several places in Scandinavia.
{"title":"Exploratory analysis of citizen observations of hourly precipitation over Scandinavia","authors":"C. Lussana, Emma Baietti, Line Båserud, T. Nipen, I. Seierstad","doi":"10.5194/asr-20-35-2023","DOIUrl":"https://doi.org/10.5194/asr-20-35-2023","url":null,"abstract":"Abstract. We present a comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national meteorological services, the latter used as reference values. The empirical distributions of the crowdsourced observations in the surroundings of reference stations are used to assess accuracy and precision of crowdsourced data. We found that reference values are typically within the distribution of the crowdsourced data. However, as the amount of precipitation increases, the spread of the crowdsourced distribution increases and the reference values are more and more frequently found towards the right tail of the distribution. These results indicate that accuracy and precision of crowdsourced data change as precipitation increases. We have studied the sensitivity of our results to the size of the neighbourhood chosen around the reference stations and we show that by aggregating the values over those neighbourhoods, crowdsourced data can be trusted in determining precipitation occurrence. We have assessed the variability of precipitation within small neighbourhoods (of radius 1, 3 and 5 km) and we provide estimates on the basis of the precipitation amounts. Our study quantifies the variability of hourly precipitation over small regions, of the size of the so-called “unresolved spatial scales” in limited area models, based on three years of data collected at several places in Scandinavia.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79589957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. This research produced gridded datasets and maps for use in building design standards to enhance resilience in support of climate change adaptation in Ireland. The new isothermal maps of return values of maximum and minimum air temperatures at mean sea level for 50, 100 and 120-year return periods based on the generalised extreme value distribution will be crucial to inform the design of buildings and bridges. The warming of the maximum and minimum air temperatures due to climate change has increased the intensity of the highest maximum air temperature while decreasing the intensity of the lowest extreme minimum air temperature of the new isothermal maps compared to previously published maps for a 50-year return period. Specifically, the new extreme isotherms are 32 ∘C for the maximum air temperature and −14 ∘C for the minimum air temperature, whereas the processor maps presented 30 and −16 ∘C, respectively. The geographical distribution of the isotherms for the 120-year return period range from 28 to 34 ∘C for the maximum air temperature and from −6 to −18 ∘C for the minimum air temperature. For the first time, isothermal maps of return values of the lowest 10 cm soil temperature for 50, 100 and 120-year return periods based on the generalised extreme value distribution have been produced for Ireland. The results presented here will be paramount to supporting the design of building structures. The values of the 120-year return period range from 0 to −2 ∘C. The produced maps represent the worst-case scenario in the current context of climate warming. The new maps of return values of snow loading at 100 m above mean sea level for 50, 100 and 120-year return periods based on the generalised Pareto distribution will be indispensable to support the design of buildings and civil engineering works such as roof patterns or bridges. The values of the 50-year return period map present four classes spread North-East to South-West: < 0.3, 0.3–0.4, 0.4–0.5 and 0.5–0.6 kN m−2, which is more accurate than the previously published map. It is expected that the comprehensive explanation of the methods and the rationale for the new maps presented here as being more accurate than the preceding maps will assist regulators in adopting these new maps in their own jurisdictions. Furthermore, these new maps will be of interest to a diversity of sectors, planners and policymakers to make long, lasting and climate-based sensitive decisions.
{"title":"Return values of temperature and snow loadings for 50, 100 and 120-year return periods to support building design standards in Ireland","authors":"C. Mateus, B. Coonan","doi":"10.5194/asr-20-17-2023","DOIUrl":"https://doi.org/10.5194/asr-20-17-2023","url":null,"abstract":"Abstract. This research produced gridded datasets and maps for use in building design\u0000standards to enhance resilience in support of climate change adaptation in\u0000Ireland. The new isothermal maps of return values of maximum and minimum air\u0000temperatures at mean sea level for 50, 100 and 120-year return periods based\u0000on the generalised extreme value distribution will be crucial to inform the\u0000design of buildings and bridges. The warming of the maximum and minimum air\u0000temperatures due to climate change has increased the intensity of the\u0000highest maximum air temperature while decreasing the intensity of the lowest\u0000extreme minimum air temperature of the new isothermal maps compared to\u0000previously published maps for a 50-year return period. Specifically, the new\u0000extreme isotherms are 32 ∘C for the maximum air temperature and\u0000−14 ∘C for the minimum air temperature, whereas the processor maps\u0000presented 30 and −16 ∘C, respectively. The\u0000geographical distribution of the isotherms for the 120-year return period\u0000range from 28 to 34 ∘C for the maximum air\u0000temperature and from −6 to −18 ∘C for the minimum air\u0000temperature. For the first time, isothermal maps of return values of the lowest 10 cm\u0000soil temperature for 50, 100 and 120-year return periods based on the\u0000generalised extreme value distribution have been produced for Ireland. The\u0000results presented here will be paramount to supporting the design of\u0000building structures. The values of the 120-year return period range from\u00000 to −2 ∘C. The produced maps represent the\u0000worst-case scenario in the current context of climate warming. The new maps of return values of snow loading at 100 m above mean sea\u0000level for 50, 100 and 120-year return periods based on the generalised\u0000Pareto distribution will be indispensable to support the design of buildings\u0000and civil engineering works such as roof patterns or bridges. The values of\u0000the 50-year return period map present four classes spread North-East to\u0000South-West: < 0.3, 0.3–0.4, 0.4–0.5 and 0.5–0.6 kN m−2,\u0000which is more accurate than the previously published map. It is expected that the comprehensive explanation of the methods and the\u0000rationale for the new maps presented here as being more accurate than the\u0000preceding maps will assist regulators in adopting these new maps in their\u0000own jurisdictions. Furthermore, these new maps will be of interest to a\u0000diversity of sectors, planners and policymakers to make long, lasting and\u0000climate-based sensitive decisions.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88224030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Cegnar, H. Boogaard, K. Finkele, B. Lalic, Joanna Raymond, Saskia Lifka, David M. Schultz, V. Tarchiani
Abstract. Agrometeorological services are a subset of climate services targeted to support farmers' tactical and strategic decisions, with the potential to support farmers' capacity to cope with climate variability and change, as well as strengthen their resilience toward climatic risks. However, the effectiveness of such services is often limited by inadequate and unsuitable means of communication with farmers. Therefore, in recent years, the World Meteorological Organization (WMO) and partners have focussed their efforts on improving communication through these services. At the European Meteorological Society (EMS) Annual Meeting in September 2022, a workshop on effective communication of agrometeorological services was held as a hybrid side event, with the aim of answering the question: “How can we deliver efficient and effective agrometeorological services”? The workshop was a joint endeavour of Met Éireann, the International Society of Biometeorology, the EMS Media and Communication Committee, the Slovenian Environment Agency, the Slovenian Meteorological Society, and the S. W. Tromp Foundation. The aim of this workshop was to advance better communication of services to the agriculture sector as a basis for promoting adaptive strategies for weather and climate change, which would enable sufficient food production at present and in the future. The workshop also provided an opportunity for transdisciplinary discussions between national meteorological and hydrological services, universities, research institutes, private companies, and the WMO. The topics discussed at the workshop included learning about exemplar agrometeorological services at various national hydrometeorological services, strengthening communication of agrometeorological services to end-users, improving data and information sharing, and educating end-users. The workshop resulted in a list of recommendations for the future.
{"title":"Toward effective communication of agrometeorological services","authors":"T. Cegnar, H. Boogaard, K. Finkele, B. Lalic, Joanna Raymond, Saskia Lifka, David M. Schultz, V. Tarchiani","doi":"10.5194/asr-20-9-2023","DOIUrl":"https://doi.org/10.5194/asr-20-9-2023","url":null,"abstract":"Abstract. Agrometeorological services are a subset of climate services targeted to support farmers' tactical and strategic decisions, with the potential to support farmers' capacity to cope with climate variability and change, as well as strengthen their resilience toward climatic risks. However, the effectiveness of such services is often limited by inadequate and unsuitable means of communication with farmers. Therefore, in recent years, the World Meteorological Organization (WMO) and partners have focussed their efforts on improving communication through these services. At the European Meteorological Society (EMS) Annual Meeting in September 2022,\u0000a workshop on effective communication of agrometeorological services was\u0000held as a hybrid side event, with the aim of answering the question: “How\u0000can we deliver efficient and effective agrometeorological services”? The\u0000workshop was a joint endeavour of Met Éireann, the International Society\u0000of Biometeorology, the EMS Media and Communication Committee, the Slovenian\u0000Environment Agency, the Slovenian Meteorological Society, and the S. W. Tromp Foundation. The aim of this workshop was to advance better\u0000communication of services to the agriculture sector as a basis for promoting\u0000adaptive strategies for weather and climate change, which would enable\u0000sufficient food production at present and in the future. The workshop also\u0000provided an opportunity for transdisciplinary discussions between national\u0000meteorological and hydrological services, universities, research institutes,\u0000private companies, and the WMO. The topics discussed at the workshop\u0000included learning about exemplar agrometeorological services at various\u0000national hydrometeorological services, strengthening communication of\u0000agrometeorological services to end-users, improving data and information\u0000sharing, and educating end-users. The workshop resulted in a list of\u0000recommendations for the future.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74277696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Iason Markantonis, D. Vlachogiannis, A. Sfetsos, I. Kioutsioukis, N. Politi
Abstract. Climate change is set to affect extreme climate and meteorological events. The combination of interacting physical processes (climate drivers) across various spatial and temporal scales resulting to an extreme event is referred to as compound event. The complex geography and topography of Greece forms a variety of regions with different local climate conditions affecting the daily minimum temperature and precipitation distributions and subsequently the distribution of compound events of low temperature and high precipitation values. The aim of our study in this work is to identify these wet–cold events based on observational data from the Hellenic National Meteorological Service (HNMS) stations, which are divided into five different geographical categories, in the period 1980–2004 and coldest months of the year (November-April) on monthly basis. Two available reanalysis products, that of ERA-Interim downscaled with the Weather Research and Forecasting (WRF) model at 5km horizontal resolution (WRF_5), and the coarser resolution (∼30 km) ERA5 Reanalysis dataset from European Centre for Medium-Range Weather Forecasts (ECMWF), are adopted to derive a gridded monthly spatial distribution of wet–cold compound events, after performing a comparison with the observations. The results yield that the monthly maximum HNMS probabilities range from 0.07 % in April to 0.85 % in February, ERA5 range from 0.4 % in April to 2.97 % in February and WRF_5 from 10.4 % in November to 25.04 % in February. The results also displayed that February, January and December, are in this order, the months with the highest WCCEs.
{"title":"Spatiotemporal investigation of wet–cold compound events in Greece","authors":"Iason Markantonis, D. Vlachogiannis, A. Sfetsos, I. Kioutsioukis, N. Politi","doi":"10.5194/asr-19-145-2023","DOIUrl":"https://doi.org/10.5194/asr-19-145-2023","url":null,"abstract":"Abstract. Climate change is set to affect extreme climate and meteorological events. The combination of interacting physical processes (climate drivers) across various spatial and temporal scales resulting to an extreme event is referred to as compound event. The complex geography and topography of Greece forms a variety of regions with different local climate conditions affecting the daily minimum temperature and precipitation distributions and subsequently the distribution of compound events of low temperature and high precipitation values. The aim of our study in this work is to identify these wet–cold events based on observational data from the Hellenic National Meteorological Service (HNMS) stations, which are divided into five different geographical categories, in the period 1980–2004 and coldest months of the year (November-April) on monthly basis. Two available\u0000reanalysis products, that of ERA-Interim downscaled with the Weather\u0000Research and Forecasting (WRF) model at 5km horizontal resolution\u0000(WRF_5), and the coarser resolution (∼30 km) ERA5 Reanalysis dataset from European Centre for Medium-Range Weather Forecasts (ECMWF), are adopted to derive a gridded monthly spatial distribution of wet–cold compound events, after performing a comparison with the observations. The results yield that the monthly maximum HNMS probabilities range from 0.07 % in April to 0.85 % in February, ERA5 range from 0.4 % in April to 2.97 % in February and WRF_5 from 10.4 % in November to 25.04 % in February. The results also displayed that February, January and December, are in this order, the months with the highest WCCEs.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75117807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Vourlioti, S. Kotsopoulos, Theano Mamouka, Apostolos Agrafiotis, Francisco Javier Nieto, Carlos Fernández Sánchez, Cecilia Grela Llerena, Sergio García González
Abstract. To promote cloud and HPC computing, GRAPEVINE* project objectives include using these tools along with open data sources to provide a reusable IT service. In this service a predictive model based on Machine learning (ML) techniques is created with the aim of preventing and controlling grape vine diseases in the wine cultivation sector. Aside from the predictive ML, meteorological forecasts are crucial input to train the ML models and on a second step to be used as input for the operational prediction of grapevine diseases. To this end, the Weather and Research Forecasting model (WRF) has been deployed in CESGA's HPC infrastructure to produce medium-range and sub-seasonal forecasts for the targeted pilot areas (Greece and Spain). The data assimilation component of WRF – WRFDA – has been also introduced for improving the initial conditions of the WRF model by assimilating observations from weather stations and satellite precipitation products (Integrated Multi-satellitE Retrieval for GPM – IMERG). This methodology for assimilation was developed during STARGATE* project, allowing the testing of the methodology in the operational service of GRAPEVINE. The operational production of the forecasts is achieved by the cloudify orchestrator on a Kubernetes cluster. The connections between the Kubernetes cluster and the HPC infrastructure, where the model resides, is achieved with the croupier plugin of cloudify. Blueprints that encapsule the workflows of the meteorological model and its dependencies were created. The instances of the blueprints (deployments) were created automatically to produce operationally weather forecasts and they were made available to the ML models via a THREDDS server. Valuable lessons were learned with regards the automation of the process and the coupling with the HPC in terms of reservations and operational production.
摘要为了促进云计算和高性能计算，GRAPEVINE*项目的目标包括使用这些工具和开放数据源来提供可重用的IT服务。在这项服务中，基于机器学习(ML)技术的预测模型被创建，目的是预防和控制葡萄酒种植部门的葡萄藤疾病。除了预测性机器学习，气象预报是训练机器学习模型的关键输入，第二步是用作葡萄藤病害操作预测的输入。为此，天气和研究预报模型(WRF)已部署在CESGA的高性能计算基础设施中，为目标试点地区(希腊和西班牙)提供中期和分季节预报。为了通过同化来自气象站和卫星降水产品的观测数据来改善WRF模式的初始条件，还引入了WRF的数据同化成分WRFDA (Integrated Multi-satellitE Retrieval for GPM - IMERG)。这种同化方法是在STARGATE*项目期间开发的，允许在GRAPEVINE的操作服务中测试该方法。预测的操作生产是由Kubernetes集群上的cloudify编排器实现的。Kubernetes集群和模型所在的HPC基础设施之间的连接是通过cloudify的croupier插件实现的。创建了封装气象模型及其依赖关系的工作流的蓝图。蓝图(部署)的实例被自动创建，以生成可操作的天气预报，并通过THREDDS服务器提供给ML模型。在过程自动化方面，以及在保留和运营生产方面与HPC的耦合方面，吸取了宝贵的经验教训。
{"title":"Maximizing the potential of numerical weather prediction models: lessons learned from combining high-performance computing and cloud computing","authors":"P. Vourlioti, S. Kotsopoulos, Theano Mamouka, Apostolos Agrafiotis, Francisco Javier Nieto, Carlos Fernández Sánchez, Cecilia Grela Llerena, Sergio García González","doi":"10.5194/asr-20-1-2023","DOIUrl":"https://doi.org/10.5194/asr-20-1-2023","url":null,"abstract":"Abstract. To promote cloud and HPC computing, GRAPEVINE* project objectives include using these tools along with open data sources to provide a reusable IT service. In this service a predictive model based on Machine learning (ML) techniques is created with the aim of preventing and\u0000controlling grape vine diseases in the wine cultivation sector. Aside from\u0000the predictive ML, meteorological forecasts are crucial input to train the\u0000ML models and on a second step to be used as input for the operational\u0000prediction of grapevine diseases. To this end, the Weather and Research\u0000Forecasting model (WRF) has been deployed in CESGA's HPC infrastructure to\u0000produce medium-range and sub-seasonal forecasts for the targeted pilot areas (Greece and Spain). The data assimilation component of WRF – WRFDA – has been also introduced for improving the initial conditions of the WRF model by assimilating observations from weather stations and satellite\u0000precipitation products (Integrated Multi-satellitE Retrieval for GPM – IMERG). This methodology for assimilation was developed during STARGATE* project, allowing the testing of the methodology in the operational service of GRAPEVINE. The operational production of the forecasts is achieved by the cloudify orchestrator on a Kubernetes cluster. The connections between the Kubernetes cluster and the HPC infrastructure, where the model resides, is achieved with the croupier plugin of cloudify. Blueprints that encapsule the workflows of the meteorological model and its dependencies were created. The instances of the blueprints (deployments) were created automatically to produce operationally weather forecasts and they were made available to the ML models via a THREDDS server. Valuable lessons were learned with regards the automation of the process and the coupling with the HPC in terms of reservations and operational production.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86901538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Small-scale processes in atmospheric boundary layers are typically not resolved due to cost constraints but modeled based on physical relations with the resolved scales, neglecting expensive backscatter. This lack in modeling is addressed in the present study with the aid of the one-dimensional turbulence (ODT) model. ODT is applied as stand-alone column model to numerically investigate stratification effects in long-lived transient Ekman flows as canonical example of polar boundary layers by resolving turbulent winds and fluctuating temperature profiles on all relevant scales of the flow. We first calibrate the adjustable model parameters for neutral cases based on the surface drag law which yields slightly different optimal model set-ups for finite low and moderate Reynolds numbers. For the stably stratified cases, previously calibrated parameters are kept fixed and the model predictions are compared with various reference numerical simulations and also observations by an exploitation of boundary layer similarity. ODT reasonably captures the temporally developing flow for various prescribed stratification profiles, but fails to fully capture the near-surface laminarization by remaining longer in a fully developed turbulent state, which suggests preferential applicability to high-Reynolds-number flow regimes. Nevertheless, the model suggests that large near-surface turbulence scales are primarily affected by the developing stratification due to scale-selective buoyancy damping which agrees with the literature. The variability of the wind-turning angle represented by the ensemble of stratified cases simulated covers a wider range than reference reanalysis data. The present study suggests that the vertical-column ODT formulation that is highly resolved in space and time can help to accurately represent multi-physics boundary-layer and subgrid-scale processes, offering new opportunities for analysis of very stable polar boundary layer and atmospheric chemistry applications.
{"title":"Exploring stratification effects in stable Ekman boundary layers using a stochastic one-dimensional turbulence model","authors":"M. Klein, H. Schmidt","doi":"10.5194/asr-19-117-2022","DOIUrl":"https://doi.org/10.5194/asr-19-117-2022","url":null,"abstract":"Abstract. Small-scale processes in atmospheric boundary layers are typically not resolved due to cost constraints but modeled based on physical relations with the resolved scales, neglecting expensive backscatter.\u0000This lack in modeling is addressed in the present study with the aid of the one-dimensional turbulence (ODT) model.\u0000ODT is applied as stand-alone column model to numerically investigate stratification effects in long-lived transient Ekman flows as canonical example of polar boundary layers by resolving turbulent winds and fluctuating temperature profiles on all relevant scales of the flow.\u0000We first calibrate the adjustable model parameters for neutral cases based on the surface drag law which yields slightly different optimal model set-ups for finite low and moderate Reynolds numbers.\u0000For the stably stratified cases, previously calibrated parameters are kept fixed and the model predictions are compared with various reference numerical simulations and also observations by an exploitation of boundary layer similarity.\u0000ODT reasonably captures the temporally developing flow for various prescribed stratification profiles, but fails to fully capture the near-surface laminarization by remaining longer in a fully developed turbulent state, which suggests preferential applicability to high-Reynolds-number flow regimes.\u0000Nevertheless, the model suggests that large near-surface turbulence scales are primarily affected by the developing stratification due to scale-selective buoyancy damping which agrees with the literature.\u0000The variability of the wind-turning angle represented by the ensemble of stratified cases simulated covers a wider range than reference reanalysis data.\u0000The present study suggests that the vertical-column ODT formulation that is highly resolved in space and time can help to accurately represent multi-physics boundary-layer and subgrid-scale processes, offering new opportunities for analysis of very stable polar boundary layer and atmospheric chemistry applications.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"101 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80614354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Tamayo, E. Rodríguez‐Camino, Alfonso Hernanz, S. Covaleda
Abstract. The intersectoral workshop held in December 2016 among the Ibero-American networks on water, climate change and meteorology, identified the need of downscaled climate change scenarios for Central America. Such scenarios would be developed by National Meteorological and Hydrological Services in the region, based on a common methodology, allowing the assessment of climate change impacts on water resources and extreme hydro-meteorological events. This project was supported by the International and Ibero-American Foundation for Administration and Public Policies of Spain in the framework of the EUROCLIMA+ programme. One final outcome of the project has been a freely accessible web viewer, installed on the Centro Clima webpage (https://centroclima.org/escenarios-cambio-climatico/, last access: 26 September 2022), managed by the Regional Committee on Hydraulic Resources of the Central American Integration System, where all information generated during the project is available for consultation and data downloading by the different sectors of users. A key element in this project has been to integrate many downscaled projections based on different methods (dynamical and statistical), totalizing 45 different projections, and aiming at estimating the uncertainty coming from different sources in the best possible way. Another essential element has been the strong involvement of the different user sectors through national workshops, first, at the beginning of the project for the identification and definition of viewer features, and then for the presentation of results and planning of its use by prioritized sectors. In a second phase of the project, a regional working group made up of experts from the participating National Meteorological and Hydrological Services will be in charge of viewer maintenance and upgrade, including new sectoral parameters, developed in collaboration with interested users, and computation and addition of new downscaled projections from CMIP6 in collaboration with the State Meteorological Agency of Spain.
{"title":"Downscaled climate change scenarios for Central America","authors":"J. Tamayo, E. Rodríguez‐Camino, Alfonso Hernanz, S. Covaleda","doi":"10.5194/asr-19-105-2022","DOIUrl":"https://doi.org/10.5194/asr-19-105-2022","url":null,"abstract":"Abstract. The intersectoral workshop held in December 2016 among the Ibero-American\u0000networks on water, climate change and meteorology, identified the need of\u0000downscaled climate change scenarios for Central America. Such scenarios\u0000would be developed by National Meteorological and Hydrological Services in\u0000the region, based on a common methodology, allowing the assessment of\u0000climate change impacts on water resources and extreme hydro-meteorological\u0000events. This project was supported by the International and Ibero-American\u0000Foundation for Administration and Public Policies of Spain in the framework\u0000of the EUROCLIMA+ programme. One final outcome of the project has been a\u0000freely accessible web viewer, installed on the Centro Clima webpage\u0000(https://centroclima.org/escenarios-cambio-climatico/, last access: 26 September 2022), managed by the Regional Committee on Hydraulic Resources of the Central American Integration System, where all information generated during the project is available for consultation and data downloading by the different sectors of users. A key element in this project has been to integrate many downscaled\u0000projections based on different methods (dynamical and statistical),\u0000totalizing 45 different projections, and aiming at estimating the\u0000uncertainty coming from different sources in the best possible way. Another\u0000essential element has been the strong involvement of the different user\u0000sectors through national workshops, first, at the beginning of the project\u0000for the identification and definition of viewer features, and then for the\u0000presentation of results and planning of its use by prioritized sectors. In a second phase of the project, a regional working group made up of\u0000experts from the participating National Meteorological and Hydrological\u0000Services will be in charge of viewer maintenance and upgrade, including new\u0000sectoral parameters, developed in collaboration with interested users, and\u0000computation and addition of new downscaled projections from CMIP6 in\u0000collaboration with the State Meteorological Agency of Spain.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78939274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Impact-based forecasts and warnings (IBFs) are seen as important drivers for adequate anticipation and assessment of potential threats to public safety as they give a better understanding of the weather event's impacts. To prepare for impacts of weather events and prevent weather-related accidents, road maintenance services are actively using weather information in their daily work routine. This paper looks into the requirements that road maintenance services have for IBFs and how weather forecasts are used at the moment. The study is part of an interdisciplinary research project and follows a qualitative social science research approach. Findings show that the following factors are general user requirements: relevance of information, recognition of spatial and temporal requests, acceptability, comprehensibility, and technical demands. These are also applicable to IBFs with the extension to provide a benefit for road maintenance services in situations that rarely occur and where no embodied knowledge in the organization is existent.
{"title":"Requirements for the use of impact-based forecasts and warnings by road maintenance services in Germany","authors":"Jasmina Schmidt, N. Tietze, L. Gerhold, T. Kox","doi":"10.5194/asr-19-97-2022","DOIUrl":"https://doi.org/10.5194/asr-19-97-2022","url":null,"abstract":"Abstract. Impact-based forecasts and warnings (IBFs) are seen as important drivers for adequate anticipation and assessment of potential threats to public safety as they give a better understanding of the weather event's impacts. To prepare for impacts of weather events and prevent weather-related accidents, road maintenance services are actively using weather information in their daily work routine. This paper looks into the requirements that road maintenance services have for IBFs and how weather forecasts are used at the\u0000moment. The study is part of an interdisciplinary research project and\u0000follows a qualitative social science research approach. Findings show that\u0000the following factors are general user requirements: relevance of\u0000information, recognition of spatial and temporal requests, acceptability,\u0000comprehensibility, and technical demands. These are also applicable to IBFs\u0000with the extension to provide a benefit for road maintenance services in\u0000situations that rarely occur and where no embodied knowledge in the\u0000organization is existent.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85212759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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