Claire Thomas, S. Dorling, William Wandji Nyamsi, L. Wald, S. Rubino, L. Saboret, Mélodie Trolliet, E. Wey
Abstract. This paper assesses several methods for the retrieval of Photosynthetically Active Radiation (PAR) from satellite imagery. The results of five different methods are compared to coincident in-situ measurements collected at three sites in southern UK. PAR retrieval methods are separated into two distinct groups. The first group comprises three methods that compute PAR by multiplying the satellite-retrieved solar broadband irradiance at the surface (SSI) by a constant coefficient. The two methods in the second group are based on more sophisticated modelling of the radiative transfer in the atmosphere involving advanced global aerosol property analyses and physically consistent total column water vapour and ozone produced by the Copernicus Atmosphere Monitoring Service (CAMS). Both methods compute a cloud modification factor from satellite-retrieved SSI. The five methods have been applied to two satellite-retrieved SSI datasets: HelioClim-3 version 5 (HC3v5) and CAMS Radiation Service (CAMS-Rad). Except at the seashore site, Group 2 methods combined with the cloud extinction from the HC3v5 dataset deliver the best results with small biases of −5 to 0 µmol m−2 s−1 (−1 % to 0 % relative to the mean of the measurements), root mean square errors of 130 µmol m−2 s−1 (28 %) and correlation coefficients exceeding 0.945. For all methods, best results are attained with the HC3v5 data set. These results demonstrate that all methods capture the temporal and spatial variability of the PAR irradiation field well, although several methods require a posteriori bias adjustments for reliable results. Combined with such an adjustment, the Udo et Aro method is a good compromise for this geographical area in terms of reliability, tractability and its ability to run in real-time. Overall, the method performing a spectral discretization in cloud-free conditions, combined with the HC3v5 dataset, outperforms other methods and has great potential for supporting an operational system.
摘要本文评价了从卫星影像中提取光合有效辐射(PAR)的几种方法。五种不同方法的结果与在英国南部三个地点收集的一致的原位测量结果进行了比较。PAR检索方法分为两个不同的组。第一组包括三种计算par的方法，即将卫星检索到的太阳表面宽带辐照度(SSI)乘以一个常数系数。第二组中的两种方法是基于更复杂的大气辐射传输模型，包括先进的全球气溶胶特性分析和白尼大气监测服务(CAMS)产生的物理一致的总柱水蒸气和臭氧。这两种方法都是根据卫星反演的SSI计算云的改变因子。将这五种方法应用于两个卫星检索的SSI数据集:helioclin -3version 5 (HC3v5)和CAMS Radiation Service (CAMS- rad)。除岸线外，第2组方法结合hc3v5数据集的云消光提供了最佳结果，偏差较小，为- 5至0µmol m - 2 s - 1(相对于测量平均值的- 1%至0%)，均方根误差为130µmol m - 2 s - 1(28%)，相关系数超过0.945。对于所有方法，使用HC3v5数据集获得最佳结果。这些结果表明，所有方法都能很好地捕捉PAR辐照场的时空变异性，尽管有些方法需要对后验偏差进行调整才能获得可靠的结果。结合这种调整，Udo et Aro方法在可靠性、可追溯性和实时运行能力方面是该地理区域的一个很好的折衷方案。总的来说，在无云条件下进行光谱离散化的方法，结合HC3v5数据集，优于其他方法，并且具有支持操作系统的巨大潜力。
{"title":"Assessment of five different methods for the estimation of surface photosynthetically active radiation from satellite imagery at three sites – application to the monitoring of indoor soft fruit crops in southern UK","authors":"Claire Thomas, S. Dorling, William Wandji Nyamsi, L. Wald, S. Rubino, L. Saboret, Mélodie Trolliet, E. Wey","doi":"10.5194/asr-16-229-2019","DOIUrl":"https://doi.org/10.5194/asr-16-229-2019","url":null,"abstract":"Abstract. This paper assesses several methods for the retrieval of Photosynthetically\u0000Active Radiation (PAR) from satellite imagery. The results of five different methods are compared to coincident in-situ measurements collected at three sites in southern UK. PAR retrieval methods are separated into\u0000two distinct groups. The first group comprises three methods that compute\u0000PAR by multiplying the satellite-retrieved solar broadband irradiance at the surface (SSI) by a constant coefficient. The two methods in the second group are based on more sophisticated modelling of the radiative transfer in the atmosphere involving advanced global aerosol property analyses and\u0000physically consistent total column water vapour and ozone produced by the\u0000Copernicus Atmosphere Monitoring Service (CAMS). Both methods compute a\u0000cloud modification factor from satellite-retrieved SSI. The five methods\u0000have been applied to two satellite-retrieved SSI datasets: HelioClim-3\u0000version 5 (HC3v5) and CAMS Radiation Service (CAMS-Rad). Except at the\u0000seashore site, Group 2 methods combined with the cloud extinction from the\u0000HC3v5 dataset deliver the best results with small biases of −5 to 0 µmol m−2 s−1 (−1 % to 0 % relative to the mean of the measurements), root mean square errors of 130 µmol m−2 s−1 (28 %) and correlation coefficients exceeding 0.945. For all methods, best results are attained with the HC3v5 data set. These results demonstrate that all methods capture the temporal and spatial variability of the PAR irradiation field well, although several methods require a posteriori bias adjustments for reliable results. Combined with such an adjustment, the Udo et Aro method is a good compromise for this geographical area in terms of reliability, tractability and its ability to run in real-time. Overall, the method performing a spectral discretization in cloud-free conditions, combined with the HC3v5 dataset, outperforms other methods and has great potential for supporting an operational system.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89079756","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. Meteorological observations are indispensable for the initialization of numerical weather prediction (NWP) forecast. To enable the application of observations in NWP models a technical preprocessing is necessary. Within the framework of RC LACE (Regional Cooperation for Limited Area modelling in Central Europe) consortium, a common observation preprocessing system (OPLACE) has been built up to deliver meteorological observations in an appropriate format for data assimilation in the NWP system ALADIN (Air Limiteée Adaptation Dynamique Développment International) The purpose of this paper is to document the OPLACE data sources, preprocessing steps and means to make preprocessed observations available. Furthermore, it describes an exchange of dense national surface synoptic measurements and high-resolution aircraft data in real-time among RC LACE national meteorological services (NMS) of Austria, Croatia, the Czech Republic, Hungary, Romania, Slovakia, and Slovenia.
{"title":"Observation Preprocessing System for RC LACE (OPLACE)","authors":"A. Trojáková, M. Mile, M. Tudor","doi":"10.5194/asr-16-223-2019","DOIUrl":"https://doi.org/10.5194/asr-16-223-2019","url":null,"abstract":"Abstract. Meteorological observations are indispensable for the initialization of numerical weather prediction (NWP) forecast.\u0000To enable the application of observations in NWP models a technical preprocessing is necessary.\u0000Within the framework of RC LACE\u0000(Regional Cooperation for Limited Area modelling in Central Europe) consortium,\u0000a common observation preprocessing system (OPLACE) has been built up to deliver\u0000meteorological observations in an appropriate format for data assimilation in the NWP system ALADIN (Air Limiteée Adaptation Dynamique Développment International)\u0000The purpose of this paper is to document the OPLACE data sources, preprocessing steps\u0000and means to make preprocessed observations available.\u0000Furthermore, it describes an exchange of dense national surface synoptic measurements and high-resolution aircraft data in real-time among RC LACE national meteorological services (NMS) of Austria, Croatia, the Czech Republic, Hungary, Romania, Slovakia, and Slovenia.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75375860","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. From 1 May 2017 until 15 June 2017, the E-AMDAR operational service from EUMETNET disseminated more commercial aircraft data than usual on the Global Telecommunication System (GTS). Météo-France specifically requested the implementation of such a trial. It lead to an increase in the number of aircraft data over France, especially vertical profiles (ascents and descents). Though Météo-France routinely buys additional data with respect to the basic E-AMDAR service, this trial aimed at assessing the potential of French airlines to produce further data in collaboration with E-AMDAR and yield an observation network as dense as possible. This was the opportunity to check the impact of these additional data on forecast skill scores of the limited area and convective scale model AROME-France. A data denial experiment (OSE) was carried out on May 2017, by removing E-AMDAR profiles (about 14 % of data) to mimic the routine observing system. The reference was the operational AROME-France 3D-Var that assimilated all extra data in real-time. However, no dedicated flag allowed to distinguish supplementary data from routine ones. Therefore, a necessary step of the experimental methodology was to identify which data profile could be considered as supplementary. The examination of forecast skill scores from the denial experiment showed that the impact of the removal of the additional observations is rather small and mixed, depending upon the parameter of interest, the atmospheric level, and the forecast range. The case studies done did not exhibit any particular additional skill for the suite with augmented observations. The experimental set-up is described and the results are discussed on the basis of forecast scores, including precipitation scores. Finally, a number of recommendations are given for a more optimal assimilation of AMDAR data in the AROME-France model.
{"title":"Impact of additional AMDAR data in the AROME-France model during May 2017","authors":"A. Doerenbecher, J. Mahfouf","doi":"10.5194/asr-16-215-2019","DOIUrl":"https://doi.org/10.5194/asr-16-215-2019","url":null,"abstract":"Abstract. From 1 May 2017 until 15 June 2017, the E-AMDAR operational service from EUMETNET disseminated more commercial aircraft data than usual on the Global Telecommunication System (GTS). Météo-France specifically requested the implementation of such a trial. It lead to an increase in the number of aircraft data over France, especially vertical profiles (ascents and descents). Though Météo-France routinely buys additional data with respect to the basic E-AMDAR service, this trial aimed at assessing the potential of French airlines to produce further data in collaboration with E-AMDAR and yield an observation network as dense as possible.\u0000This was the opportunity to check the impact of these additional data on forecast skill scores of the limited area and convective scale model AROME-France. A data denial experiment (OSE) was carried out on May 2017, by removing E-AMDAR profiles (about 14 % of data) to mimic the routine observing system. The reference was the operational AROME-France 3D-Var that assimilated all extra data in real-time. However, no dedicated flag allowed to distinguish supplementary data from routine ones. Therefore, a necessary step of the experimental methodology was to identify which data profile could be considered as supplementary. The examination of forecast skill scores from the denial experiment showed that the impact of the removal of the additional observations is rather small and mixed, depending upon the parameter of interest, the atmospheric level, and the forecast range. The case studies done did not exhibit any particular additional skill for the suite with augmented observations. The experimental set-up is described and the results are discussed on the basis of forecast scores, including precipitation scores. Finally, a number of recommendations are given for a more optimal assimilation of AMDAR data in the AROME-France model.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76695952","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}
L. Rottner, P. Arbogast, Mayeul Destouches, Yamina Hamidi, L. Raynaud
Abstract. A new object-oriented method has been developed to detect hazardous phenomena predicted by Numerical Weather Prediction (NWP) models. This method, called similarity-based method, is looking for specific meteorological objects in the forecasts, which are defined by a reference histogram representing the meteorological phenomena to be detected. The similarity-based method enables to cope with small scale unpredictable details of mesoscale structures in meteorological models and to quantify the uncertainties on the location of the predicted phenomena. Applied to ensemble forecasts, the similarity-based method can be viewed as a particular case of neighborhood processing, allowing spatialized probabilities to be computed. An application to rainfall detection using forecasts from the AROME deterministic and ensemble models is presented.
{"title":"The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts","authors":"L. Rottner, P. Arbogast, Mayeul Destouches, Yamina Hamidi, L. Raynaud","doi":"10.5194/asr-16-209-2019","DOIUrl":"https://doi.org/10.5194/asr-16-209-2019","url":null,"abstract":"Abstract. A new object-oriented method has been developed to detect hazardous phenomena predicted by Numerical Weather Prediction (NWP) models. This method, called similarity-based method, is looking for specific meteorological objects in the forecasts, which are defined by a reference histogram representing the meteorological phenomena to be detected. The similarity-based method enables to cope with small scale unpredictable details of mesoscale structures in meteorological models and to quantify the uncertainties on the location of the predicted phenomena. Applied to ensemble forecasts, the similarity-based method can be viewed as a particular case of neighborhood processing, allowing spatialized probabilities to be computed. An application to rainfall detection using forecasts from the AROME deterministic and ensemble models is presented.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85082548","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. There are many atmospheric phenomena which can be taught in the frame of different subjects at secondary schools. Geography and environmental education characteristically deal with observable natural phenomena. Some of them can be easily modeled in a school laboratory, but in spite of this neither the exact (phenomenological) description nor the theoretical background of these phenomena are given in any of the curricula. These phenomena include a wide scale of atmospheric and marine whirls. The beauty and frightening effect of the vortices from dust devils and waterspouts to hurricanes and cyclones can be a great motivating force for the students to learn more about the physics of these phenomena. This paper demonstrates the introductory steps of the elaboration of a learning material about the atmospheric eddies and shows how can be connected the formal and non-formal teaching methods. To construct the teaching material the principles of the MER (Model of Educational Reconstruction) will be applied (Niebert and Gropengiesser, 2013), having planned the educational reconstruction of the scientific content we suggest simple conceptual and mathematical description of atmospheric whirls of tornadic type at secondary school level.
{"title":"Atmospheric eddies in Science Centers – connection between secondary school teaching and informal learning","authors":"A. Király, P. Tasnádi","doi":"10.5194/asr-16-201-2019","DOIUrl":"https://doi.org/10.5194/asr-16-201-2019","url":null,"abstract":"Abstract. There are many atmospheric phenomena which can be taught\u0000in the frame of different subjects at secondary schools. Geography and\u0000environmental education characteristically deal with observable natural\u0000phenomena. Some of them can be easily modeled in a school laboratory, but in\u0000spite of this neither the exact (phenomenological) description nor the\u0000theoretical background of these phenomena are given in any of the curricula.\u0000These phenomena include a wide scale of atmospheric and marine whirls. The\u0000beauty and frightening effect of the vortices from dust devils and\u0000waterspouts to hurricanes and cyclones can be a great motivating force for\u0000the students to learn more about the physics of these phenomena. This paper\u0000demonstrates the introductory steps of the elaboration of a learning\u0000material about the atmospheric eddies and shows how can be connected the\u0000formal and non-formal teaching methods. To construct the teaching material\u0000the principles of the MER (Model of Educational Reconstruction) will be\u0000applied (Niebert and Gropengiesser, 2013), having planned the educational\u0000reconstruction of the scientific content we suggest simple conceptual and\u0000mathematical description of atmospheric whirls of tornadic type at secondary\u0000school level.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74345740","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}
Esteban Rodríguez-Guisado, Antonio Ángel Serrano-de la Torre, E. Sánchez-García, Marta Domínguez-Alonso, E. Rodríguez‐Camino
Abstract. In the frame of MEDSCOPE project, which mainly aims at improving predictability on seasonal timescales over the Mediterranean area, a seasonal forecast empirical model making use of new predictors based on a collection of targeted sensitivity experiments is being developed. Here, a first version of the model is presented. This version is based on multiple linear regression, using global climate indices (mainly global teleconnection patterns and indices based on sea surface temperatures, as well as sea-ice and snow cover) as predictors. The model is implemented in a way that allows easy modifications to include new information from other predictors that will come as result of the ongoing sensitivity experiments within the project. Given the big extension of the region under study, its high complexity (both in terms of orography and land-sea distribution) and its location, different sub regions are affected by different drivers at different times. The empirical model makes use of different sets of predictors for every season and every sub region. Starting from a collection of 25 global climate indices, a few predictors are selected for every season and every sub region, checking linear correlation between predictands (temperature and precipitation) and global indices up to one year in advance and using moving averages from two to six months. Special attention has also been payed to the selection of predictors in order to guaranty smooth transitions between neighbor sub regions and consecutive seasons. The model runs a three-month forecast every month with a one-month lead time.
{"title":"Development of an empirical model for seasonal forecasting over the Mediterranean","authors":"Esteban Rodríguez-Guisado, Antonio Ángel Serrano-de la Torre, E. Sánchez-García, Marta Domínguez-Alonso, E. Rodríguez‐Camino","doi":"10.5194/asr-16-191-2019","DOIUrl":"https://doi.org/10.5194/asr-16-191-2019","url":null,"abstract":"Abstract. In the frame of MEDSCOPE project, which mainly aims at\u0000improving predictability on seasonal timescales over the Mediterranean area,\u0000a seasonal forecast empirical model making use of new predictors based on a\u0000collection of targeted sensitivity experiments is being developed. Here, a\u0000first version of the model is presented. This version is based on multiple\u0000linear regression, using global climate indices (mainly global\u0000teleconnection patterns and indices based on sea surface temperatures, as\u0000well as sea-ice and snow cover) as predictors. The model is implemented in a\u0000way that allows easy modifications to include new information from other\u0000predictors that will come as result of the ongoing sensitivity experiments\u0000within the project. Given the big extension of the region under study, its high complexity (both\u0000in terms of orography and land-sea distribution) and its location, different\u0000sub regions are affected by different drivers at different times. The\u0000empirical model makes use of different sets of predictors for every season\u0000and every sub region. Starting from a collection of 25 global climate\u0000indices, a few predictors are selected for every season and every sub\u0000region, checking linear correlation between predictands (temperature and\u0000precipitation) and global indices up to one year in advance and using moving\u0000averages from two to six months. Special attention has also been payed to\u0000the selection of predictors in order to guaranty smooth transitions between\u0000neighbor sub regions and consecutive seasons. The model runs a three-month\u0000forecast every month with a one-month lead time.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86834549","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. Thermodynamics and electricity are parts of the 10th grade physics curriculum in Romania, but the exciting questions of atmospheric physics and meteorology could be answered if we organize special activities. Linking these topics, educators can create many interesting learning opportunities and try new ways of teaching. This paper is based on a school project and experiment that were used during the last school years in the classroom learning and practical outdoor activities with the Science Club students. The aim of the project is to build a device to measure atmospheric climate variables (e.g. air temperature, air pressure, humidity) and to demonstrate and explain some weather phenomenon. The observations are stored in a database, the data archive and visualization of the data are accessible through a webpage. Students from other schools can get involved in the measurements with their own built devices and can upload their own measurement data to the common database, so we could create a weather map for schools. The whole system is planned as a network of minimeteo stations for students.
{"title":"How to build a mini meteorological station for your school? – A project with a citizen science perspective","authors":"M. Pető, A. Király","doi":"10.5194/asr-16-185-2019","DOIUrl":"https://doi.org/10.5194/asr-16-185-2019","url":null,"abstract":"Abstract. Thermodynamics and electricity are parts of the 10th grade physics curriculum in Romania, but the exciting questions of\u0000atmospheric physics and meteorology could be answered if we organize special activities. Linking these topics, educators can create many interesting learning opportunities and try new ways of teaching. This paper is based on a school project and experiment that were used during the last school years in the classroom learning and practical outdoor activities with the Science Club students. The aim of the project is to build a device to measure atmospheric climate variables (e.g. air temperature, air pressure, humidity) and to demonstrate and explain some weather phenomenon. The observations are stored in a database, the data archive and visualization of the data are accessible through a webpage. Students from other schools can get involved in the measurements with their own built devices and can upload their own measurement data to the common database, so we could create a weather map for schools. The whole system is planned as a network of minimeteo stations for students.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74439049","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. Precise quantification of climate change depends on long time series of meteorological variables. Such time series should be as homogeneous as possible but some changes of measurement conditions cannot be prevented. At German climate reference stations, parallel measurements are used to analyze the effects of changes in measurement systems for example for the transition from manual to automatic instruments. These parallel measurements aim to identify measurement uncertainties and to analyze the comparability of measurement systems to investigate the homogeneity. In this study, we investigate daily sunshine duration. Traditionally, manual measurements of daily sunshine duration are taken with Campbell-Stokes sunshine recorders. For automatic measurements the SONIe or SCAPP instrument is used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. During summer, values for manual observations are larger especially in case of frequent alternations between sunny and cloudy conditions. Furthermore, the standard deviation of the differences between the two measurement systems is larger during summer because of the greater day length. To adjust the automatic measurements a linear regression model is suggested based on parallel measurements from 13 climate reference stations in Germany. To validate the regression coefficients, a leave-one-out cross validation was performed (by leaving out data of individual stations). The regression coefficients (derived from different sets of stations) are similar, thereby indicating a robust data set for the estimation of the linear model. With this method we want to prevent breaks in long time series of daily sunshine duration caused by the transition from manual to automatic instruments.
{"title":"Comparison of manual and automatic daily sunshine duration measurements at German climate reference stations","authors":"L. Hannak, K. Friedrich, F. Imbery, F. Kaspar","doi":"10.5194/ASR-16-175-2019","DOIUrl":"https://doi.org/10.5194/ASR-16-175-2019","url":null,"abstract":"Abstract. Precise quantification of climate change depends on long time series of meteorological variables. Such time series should be as homogeneous as possible but some changes of measurement conditions cannot be prevented. At German climate reference stations, parallel measurements are used to analyze the effects of changes in measurement systems for example for the transition from manual to automatic instruments. These parallel measurements aim to identify measurement uncertainties and to analyze the comparability of measurement systems to investigate the homogeneity. In this study, we investigate daily sunshine duration. Traditionally, manual measurements of daily sunshine duration are taken with Campbell-Stokes sunshine recorders. For automatic measurements the SONIe or SCAPP instrument is used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. During summer, values for manual observations are larger especially in case of frequent alternations between sunny and cloudy conditions. Furthermore, the standard deviation of the differences between the two measurement systems is larger during summer because of the greater day length. To adjust the automatic measurements a linear regression model is suggested based on parallel measurements from 13 climate reference stations in Germany. To validate the regression coefficients, a leave-one-out cross validation was performed (by leaving out data of individual stations). The regression coefficients (derived from different sets of stations) are similar, thereby indicating a robust data set for the estimation of the linear model. With this method we want to prevent breaks in long time series of daily sunshine duration caused by the transition from manual to automatic instruments.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80879923","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}
E. Sánchez-García, Jose Voces-Aboy, B. Navascués, E. Rodríguez‐Camino
Abstract. We describe a methodology for ensemble member's weighting of operational seasonal forecasting systems (SFS) based on an enhanced prediction of a climate driver strongly affecting meteorological parameters over a certain region. We have applied it to the North Atlantic Oscillation (NAO) influence on the Iberian Peninsula winter precipitation. The first step in the proposed approach is to find the best estimation of winter NAO. Skill and error characteristics of forecasted winter NAO index by different Copernicus SFS are analysed in this study. Based on these results, a bias correction scheme is proposed and implemented for the ECMWF System 5 ensemble mean of NAO index, and then a modified NAO index pdf based on Gaussian errors is formulated. Finally, we apply the statistical estimation theory to achieve the Best linear unbiased estimate of winter NAO index and its uncertainty. For this purpose, two a priori estimates are used: the bias corrected NAO index Gaussian pdf from ECMWF System 5, and a skilful winter NAO index prediction based on teleconnection with snow cover advance with normal distributed errors. The second step of the proposed methodology is to employ the enhanced NAO index pdf estimates for ensemble member's weighting of a SFS based on a single dynamical model. The new NAO pdfs obtained in this work have been used to improve the skill of the ECMWF System 5 to predict both NAO index and precipitation over the Iberian Peninsula. We show the improvement of NAO prediction, and of winter precipitation forecasts over our region of interest, when members are weighted with the bias corrected NAO index Gaussian pdf based on ECMWF System 5 compared with the usual approach based on equiprobability of ensemble members. Forecast skill is further enhanced if the Best NAO index pdf based on an optimal combination of the two a priori NAO index estimates is used for ensemble member's weighting.
摘要我们描述了一种基于对某一地区强烈影响气象参数的气候驱动因素的增强预测的操作性季节预报系统(SFS)的集合成员加权方法。将其应用于北大西洋涛动(NAO)对伊比利亚半岛冬季降水的影响。该方法的第一步是找到冬季NAO的最佳估计。分析了不同哥白尼SFS预测冬季NAO指数的技巧和误差特征。在此基础上，提出并实现了ECMWFSystem 5系统NAO指数集合均值的偏差校正方案，并在此基础上建立了基于高斯误差的修正NAO指数pdf。最后，应用统计估计理论对冬季NAOindex及其不确定性进行了最佳线性无偏估计。为此，使用了两个先验估计:ECMWF系统5的偏差校正后的NAO指数高斯pdf，以及基于积雪覆盖的遥相关正态分布误差的冬季NAO指数预测。该方法的第二步是采用改进的NAOindex pdf估计基于单个动态模型的SFS集成成员的权重。这项工作获得的新的NAO pdf格式已用于提高ECMWF系统5预测NAO指数和伊比利亚半岛降水的技能。与基于集合成员等概率的通常方法相比，当使用基于ECMWF System 5的偏差校正后的NAO指数高斯pdf对成员进行加权时，我们展示了naao预测的改进，以及我们感兴趣区域的冬季降水预报。基于两个先验NAO指数估计最优组合的最佳NAO指数pdf用于集合成员的加权，进一步提高了预测技能。
{"title":"Regionally improved seasonal forecast of precipitation through Best estimation of winter NAO","authors":"E. Sánchez-García, Jose Voces-Aboy, B. Navascués, E. Rodríguez‐Camino","doi":"10.5194/ASR-16-165-2019","DOIUrl":"https://doi.org/10.5194/ASR-16-165-2019","url":null,"abstract":"Abstract. We describe a methodology for ensemble member's weighting\u0000of operational seasonal forecasting systems (SFS) based on an enhanced\u0000prediction of a climate driver strongly affecting meteorological parameters\u0000over a certain region. We have applied it to the North Atlantic Oscillation\u0000(NAO) influence on the Iberian Peninsula winter precipitation. The first step in the proposed approach is to find the best estimation of\u0000winter NAO. Skill and error characteristics of forecasted winter NAO index\u0000by different Copernicus SFS are analysed in this study. Based on these\u0000results, a bias correction scheme is proposed and implemented for the ECMWF\u0000System 5 ensemble mean of NAO index, and then a modified NAO index pdf based\u0000on Gaussian errors is formulated. Finally, we apply the statistical\u0000estimation theory to achieve the Best linear unbiased estimate of winter NAO\u0000index and its uncertainty. For this purpose, two a priori estimates are\u0000used: the bias corrected NAO index Gaussian pdf from ECMWF System 5, and a\u0000skilful winter NAO index prediction based on teleconnection with snow cover\u0000advance with normal distributed errors. The second step of the proposed methodology is to employ the enhanced NAO\u0000index pdf estimates for ensemble member's weighting of a SFS based on a\u0000single dynamical model. The new NAO pdfs obtained in this work have been\u0000used to improve the skill of the ECMWF System 5 to predict both NAO index\u0000and precipitation over the Iberian Peninsula. We show the improvement of NAO\u0000prediction, and of winter precipitation forecasts over our region of\u0000interest, when members are weighted with the bias corrected NAO index\u0000Gaussian pdf based on ECMWF System 5 compared with the usual approach based\u0000on equiprobability of ensemble members. Forecast skill is further enhanced\u0000if the Best NAO index pdf based on an optimal combination of the two a\u0000priori NAO index estimates is used for ensemble member's weighting.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75793984","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}
F. Besson, B. Dubuisson, P. Etchevers, A. Gibelin, P. Lassègues, Michel Schneider, B. Vincendon
Abstract. For many years real-time climate monitoring for temperature over France has been performed using a national index built by averaging the daily mean temperatures of constant subset of 30 stations with long-term series. In order to derive climate indices at finer scales, a spatialization of extreme daily temperatures (called ANASTASIA) had been produced on a 1 km regular grid using a regression-kriging method. The production covers 1947 to present period. Cross-validation shows low biases after the 1960s. The temporal homogeneity of the product is satisfying at the national scale from the 1970s. However, a high impact of the network density has been found and the use of a too coarse observation network deteriorates the analysis creating temporal heterogeneities. Finally, the ANASTASIA analysis has been used for real-time monitoring over France and detection of heat and cold wave episodes. The new products based on ANASTASIA are consistent with the current operational ones at national scale while bringing added values at local scales.
{"title":"Climate monitoring and heat and cold waves detection over France using a new spatialization of daily temperature extremes from 1947 to present","authors":"F. Besson, B. Dubuisson, P. Etchevers, A. Gibelin, P. Lassègues, Michel Schneider, B. Vincendon","doi":"10.5194/ASR-16-149-2019","DOIUrl":"https://doi.org/10.5194/ASR-16-149-2019","url":null,"abstract":"Abstract. For many years real-time climate monitoring for temperature over France has been performed using a national index built by averaging the daily mean temperatures of constant subset of 30 stations with long-term series. In order to derive climate indices at finer scales, a spatialization of extreme daily temperatures (called ANASTASIA) had been produced on a 1 km regular grid using a regression-kriging method. The production covers 1947 to present period. Cross-validation shows low biases after the 1960s. The temporal homogeneity of the product is satisfying at the national scale from the 1970s. However, a high impact of the network density has been found and the use of a too coarse observation network deteriorates the analysis creating temporal heterogeneities. Finally, the ANASTASIA analysis has been used for real-time monitoring over France and detection of heat and cold wave episodes. The new products based on ANASTASIA are consistent with the current operational ones at national scale while bringing added values at local scales.\u0000","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82529637","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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