Pub Date : 2024-07-26DOI: 10.3103/s1068373924050054
A. I. Medvedev, V. M. Stepanenko, V. Yu. Bogomolov
Abstract
The paper investigates the sensitivity of evapotranspiration in the INM RAS–MSU land surface model to the changes in the weights of land surface classes in the cells of the latitude-longitude grid and the leaf area index LAI. It is demonstrated that the refinement of the values of the mentioned parameters based on modern observational data significantly reduces an error in evapotranspiration. The annual sum of evapotranspiration averaged over 10 years (2002–2012) from the surface of medium-sized (2−50×103 km2) watersheds of northern European Russia is used for the analysis. The model error has been calculated against the empirical estimates of evapotranspiration obtained from the watershed water balance equation. As an intermediate task, the accuracy of satellite data on terrestrial water storage used in the calculations is assessed by the comparison with the data of snow route surveys.
{"title":"Influence of External Parameters on Evapotranspiration in the INM RAS–MSU Land Surface Model","authors":"A. I. Medvedev, V. M. Stepanenko, V. Yu. Bogomolov","doi":"10.3103/s1068373924050054","DOIUrl":"https://doi.org/10.3103/s1068373924050054","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper investigates the sensitivity of evapotranspiration in the INM RAS–MSU land surface model to the changes in the weights of land surface classes in the cells of the latitude-longitude grid and the leaf area index LAI. It is demonstrated that the refinement of the values of the mentioned parameters based on modern observational data significantly reduces an error in evapotranspiration. The annual sum of evapotranspiration averaged over 10 years (2002–2012) from the surface of medium-sized (2−50×10<sup>3</sup> km<sup>2</sup>) watersheds of northern European Russia is used for the analysis. The model error has been calculated against the empirical estimates of evapotranspiration obtained from the watershed water balance equation. As an intermediate task, the accuracy of satellite data on terrestrial water storage used in the calculations is assessed by the comparison with the data of snow route surveys.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"9 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050091
K. L. Antonov, E. A. Gulyaev, Yu. I. Markelov, V. A. Poddubny
Abstract
The patterns and factors of changes in CO2 and CH4 concentrations in the surface atmosphere of an urbanized and suburban environment were analyzed based on the results of the synchronous measurements in Yekaterinburg and the Kourovka Astronomical Observatory (KAO) in September 2021–August 2022. On average, the maximum levels of CO2 in Yekaterinburg (443.2 ppm) were shown to be higher than in KAO (432.4 ppm) and were reached in January. The minima, on the contrary, were lower in the city than in the suburban area (405.4 ppm in July in Yekaterinburg against 412.7 ppm in September in KAO). Enhanced CO2 levels in the warm season in KAO were caused by very high nighttime concentrations (up to 500 ppm), which was not observed in the surface urban atmosphere. For CH4, the seasonal dynamics in the city and in KAO was similar: the maximum levels were reached in January (2.154 and 2.076 ppm), and the minima were registered in June (1.998 and 1.971 ppm). The mutual influence of the territories under consideration was assessed to be moderate. The results of the study can be used to develop a technology for assessing the carbon balances on a regional scale, which is the main task of the Carbon Supersites program in the Urals.
{"title":"Variation Patterns of CO2 and CH4 according to the Measurements in the Surface Atmosphere over Urban and Suburban Areas in 2021–2022","authors":"K. L. Antonov, E. A. Gulyaev, Yu. I. Markelov, V. A. Poddubny","doi":"10.3103/s1068373924050091","DOIUrl":"https://doi.org/10.3103/s1068373924050091","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The patterns and factors of changes in CO<sub>2</sub> and CH<sub>4</sub> concentrations in the surface atmosphere of an urbanized and suburban environment were analyzed based on the results of the synchronous measurements in Yekaterinburg and the Kourovka Astronomical Observatory (KAO) in September 2021–August 2022. On average, the maximum levels of CO<sub>2</sub> in Yekaterinburg (443.2 ppm) were shown to be higher than in KAO (432.4 ppm) and were reached in January. The minima, on the contrary, were lower in the city than in the suburban area (405.4 ppm in July in Yekaterinburg against 412.7 ppm in September in KAO). Enhanced CO<sub>2</sub> levels in the warm season in KAO were caused by very high nighttime concentrations (up to 500 ppm), which was not observed in the surface urban atmosphere. For CH<sub>4</sub>, the seasonal dynamics in the city and in KAO was similar: the maximum levels were reached in January (2.154 and 2.076 ppm), and the minima were registered in June (1.998 and 1.971 ppm). The mutual influence of the territories under consideration was assessed to be moderate. The results of the study can be used to develop a technology for assessing the carbon balances on a regional scale, which is the main task of the Carbon Supersites program in the Urals.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"37 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s106837392405008x
A. Yu. Perevaryukha
Abstract
The climate change observed in the zone of boreal forests of the Holarctic since the end of the 20th century initiates the effect of expanding the boundaries of biological species ranges. Climate-driven invasive processes differ in dynamics. In some situations, there are population outbreaks of unwanted species. In addition to the climatic factor, an important aspect is the response of a biotic environment. Special methods are required to predict rapid invasions that can cause extreme changes. The reproductive potential of pests often turns out to be excessive due to warming climate and favorable conditions. Aggressive invasions often develop as oscillating processes that transform when the species adapts to the environment and fades when the autochthonous biota adapts to a new species. Not only new pests, but also the enemies of the main enemies of ordinary pests have become harmful invaders. Computational scenario models of invasions have been developed based on a logically expandable hybrid structure of equations that take into account delayed adaptation, which is manifested depending on climatic factors as an invasion outbreak develops. The scenarios indicate the series of peaks with fading activity after a primary outbreak and make it possible to evaluate the factors that cause repeated activity of a population after a depression when the invasion of a hyperparasite turns out to be essential.
{"title":"Forecast Modeling of Invasive and Climate-driven Scenarios of Pest Outbreaks","authors":"A. Yu. Perevaryukha","doi":"10.3103/s106837392405008x","DOIUrl":"https://doi.org/10.3103/s106837392405008x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The climate change observed in the zone of boreal forests of the Holarctic since the end of the 20th century initiates the effect of expanding the boundaries of biological species ranges. Climate-driven invasive processes differ in dynamics. In some situations, there are population outbreaks of unwanted species. In addition to the climatic factor, an important aspect is the response of a biotic environment. Special methods are required to predict rapid invasions that can cause extreme changes. The reproductive potential of pests often turns out to be excessive due to warming climate and favorable conditions. Aggressive invasions often develop as oscillating processes that transform when the species adapts to the environment and fades when the autochthonous biota adapts to a new species. Not only new pests, but also the enemies of the main enemies of ordinary pests have become harmful invaders. Computational scenario models of invasions have been developed based on a logically expandable hybrid structure of equations that take into account delayed adaptation, which is manifested depending on climatic factors as an invasion outbreak develops. The scenarios indicate the series of peaks with fading activity after a primary outbreak and make it possible to evaluate the factors that cause repeated activity of a population after a depression when the invasion of a hyperparasite turns out to be essential.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"68 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050066
Ch. Meng, Y. Gu, H. Li, H. Jin, G. Zhang, J. Cui
Abstract
The leaf area index (LAI) and fractional vegetation cover (FVC) are very important parameters in land–atmosphere interactions. In this study, a very simple but robust and mechanism-based method was developed to derive FVC data based on the relationships between the canopy gap fraction, LAI, and direct solar extinction coefficient. For validation, the LAI data and NDVI-based and mechanism-based FVC data were assimilated into the integrated urban land model (IUM). Using the mechanism-based FVC data as the input, the simulation of the annual average land surface temperatures (LSTs) in the Beijing area were improved compared with those using the NDVI-based FVC data as the input.
{"title":"A Physical Mechanism-based Scheme for Parameterizing the Fractional Vegetation Cover","authors":"Ch. Meng, Y. Gu, H. Li, H. Jin, G. Zhang, J. Cui","doi":"10.3103/s1068373924050066","DOIUrl":"https://doi.org/10.3103/s1068373924050066","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The leaf area index (LAI) and fractional vegetation cover (FVC) are very important parameters in land–atmosphere interactions. In this study, a very simple but robust and mechanism-based method was developed to derive FVC data based on the relationships between the canopy gap fraction, LAI, and direct solar extinction coefficient. For validation, the LAI data and NDVI-based and mechanism-based FVC data were assimilated into the integrated urban land model (IUM). Using the mechanism-based FVC data as the input, the simulation of the annual average land surface temperatures (LSTs) in the Beijing area were improved compared with those using the NDVI-based FVC data as the input.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"38 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050029
I. S. Danilovich, M. G. Akperov, A. V. Beganskii, M. A. Dembitskaya
Abstract
The study presents the classification of cyclones according to the region of origin and track in the Euro-Atlantic sector. The cyclones have been identified according to the ERA5 reanalysis data. Their seasonal frequency, travel speed, size, and central pressure have been quantified, and their trends have been revealed. Mean and maximum total precipitation associated with the distinguished types of cyclones over the territory of Europe is determined. It is shown that the frequency of the North Atlantic cyclones in the recent 40 years has decreased in winter, summer, and autumn and increased in spring. It has been revealed, that the frequency of the southern cyclones insignificantly decreases in summer and increases in winter. A decrease in minimum central pressure for some types of the North Atlantic cyclones occurs in winter and summer. There is an increase in maximum total precipitation in winter due to the North Atlantic cyclones and in summer due to the southern cyclones. The number of days with cyclonic precipitation decreases for all types of cyclones.
{"title":"Spatiotemporal Changes in Cyclogenesis and Precipitation Regime over the Euro-Atlantic Sector in 1979–2019","authors":"I. S. Danilovich, M. G. Akperov, A. V. Beganskii, M. A. Dembitskaya","doi":"10.3103/s1068373924050029","DOIUrl":"https://doi.org/10.3103/s1068373924050029","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The study presents the classification of cyclones according to the region of origin and track in the Euro-Atlantic sector. The cyclones have been identified according to the ERA5 reanalysis data. Their seasonal frequency, travel speed, size, and central pressure have been quantified, and their trends have been revealed. Mean and maximum total precipitation associated with the distinguished types of cyclones over the territory of Europe is determined. It is shown that the frequency of the North Atlantic cyclones in the recent 40 years has decreased in winter, summer, and autumn and increased in spring. It has been revealed, that the frequency of the southern cyclones insignificantly decreases in summer and increases in winter. A decrease in minimum central pressure for some types of the North Atlantic cyclones occurs in winter and summer. There is an increase in maximum total precipitation in winter due to the North Atlantic cyclones and in summer due to the southern cyclones. The number of days with cyclonic precipitation decreases for all types of cyclones.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"122 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050042
E. V. Gorbarenko, N. A. Bunina
Abstract
The light climate of Moscow is presented based on the long-term observations of natural illuminance of the Earth’s surface, illuminance of differently oriented vertical surfaces, and factors influencing their variability, which have been performed at the Moscow State University Meteorological Observatory. The obtained normals are sufficient for any practical applications in most cases. An issue analyzed in the study is conditions that lead to a decrease in illumination below the critical values for which the use of combined or artificial lighting of premises is required. It is shown that illumination can be forecasted based on low-level clouds predicted using a general weather forecast.
{"title":"Light Climate in Moscow","authors":"E. V. Gorbarenko, N. A. Bunina","doi":"10.3103/s1068373924050042","DOIUrl":"https://doi.org/10.3103/s1068373924050042","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The light climate of Moscow is presented based on the long-term observations of natural illuminance of the Earth’s surface, illuminance of differently oriented vertical surfaces, and factors influencing their variability, which have been performed at the Moscow State University Meteorological Observatory. The obtained normals are sufficient for any practical applications in most cases. An issue analyzed in the study is conditions that lead to a decrease in illumination below the critical values for which the use of combined or artificial lighting of premises is required. It is shown that illumination can be forecasted based on low-level clouds predicted using a general weather forecast.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"94 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050017
R. M. Vil’fand, S. V. Emelina, V. A. Tischenko, M. A. Tolstykh, V. M. Khan
Abstract
For the territory of Northern Eurasia, a scheme for the statistical correction of surface air temperature forecasts has been developed for periods of 1–4 months on the basis of the SL-AV model using the MOS concept. For statistical correction of operational temperature forecasts, the regression parameters and EOF expansion coefficients obtained by cross-validation on historical forecasts were used. Due to the internal relationships of the model output data, the proposed scheme allows improving the skill of surface characteristic forecasts. A significant improvement in the skill of deterministic air temperature forecasts by using statistical correction is manifested in transition seasons. The scheme of statistical correction is constantly evolving. Further development of the statistical correction technology involves the use of neural networks and forecast indices of atmospheric circulation.
摘要 在欧亚北部地区，以 SL-AV 模式为基础，利用 MOS 概念，制定了 1-4 个月期间地表气温预报的统计校正方案。为了对业务气温预报进行统计校正，使用了通过对历史预报进行交叉验证获得的回归参数和 EOF 扩展系数。由于模式输出数据的内部关系，所提出的方案可以提高地表特征预报的技能。在过渡季节，通过使用统计校正，确定性气温预报的技能得到了明显改善。统计校正方案在不断发展。统计校正技术的进一步发展涉及到神经网络和大气环流预报指数的使用。
{"title":"Statistical Correction of the SL-AV Model Long-term Forecasts of Surface Air Temperature for the Territory of Northern Eurasia","authors":"R. M. Vil’fand, S. V. Emelina, V. A. Tischenko, M. A. Tolstykh, V. M. Khan","doi":"10.3103/s1068373924050017","DOIUrl":"https://doi.org/10.3103/s1068373924050017","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>For the territory of Northern Eurasia, a scheme for the statistical correction of surface air temperature forecasts has been developed for periods of 1–4 months on the basis of the SL-AV model using the MOS concept. For statistical correction of operational temperature forecasts, the regression parameters and EOF expansion coefficients obtained by cross-validation on historical forecasts were used. Due to the internal relationships of the model output data, the proposed scheme allows improving the skill of surface characteristic forecasts. A significant improvement in the skill of deterministic air temperature forecasts by using statistical correction is manifested in transition seasons. The scheme of statistical correction is constantly evolving. Further development of the statistical correction technology involves the use of neural networks and forecast indices of atmospheric circulation.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050030
V. F. Loginov, M. A. Khitrykau
Abstract
Average daily air temperature and daily total precipitation were analyzed using quantile regression. Quantiles corresponding to the selected extremes, i.e., below 0.1 (only for the analysis of air temperature) and above 0.9 were considered. It has been shown for the majority of cases that the spatial distribution of air temperature quantiles is close to the mean for winter and summer seasons. Specific features of temporal changes in the quantiles of air temperature and total precipitation are in line with the modern climate warming. A statistically significant relationship between air temperature and Earth surface characteristics is observed only for quantiles of 0.9 and more. Due to the complexity of the factors responsible for the formation of high-intensity precipitation, there is no clear pattern in the spatial distribution of the quantiles of daily total precipitation. There is statistically significant relationship between daily total precipitation, orography, and forest cover fraction on the territory.
{"title":"Analysis of Average Daily Temperature and Precipitation on the Territory of Belarus Using Quantile Regression","authors":"V. F. Loginov, M. A. Khitrykau","doi":"10.3103/s1068373924050030","DOIUrl":"https://doi.org/10.3103/s1068373924050030","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Average daily air temperature and daily total precipitation were analyzed using quantile regression. Quantiles corresponding to the selected extremes, i.e., below 0.1 (only for the analysis of air temperature) and above 0.9 were considered. It has been shown for the majority of cases that the spatial distribution of air temperature quantiles is close to the mean for winter and summer seasons. Specific features of temporal changes in the quantiles of air temperature and total precipitation are in line with the modern climate warming. A statistically significant relationship between air temperature and Earth surface characteristics is observed only for quantiles of 0.9 and more. Due to the complexity of the factors responsible for the formation of high-intensity precipitation, there is no clear pattern in the spatial distribution of the quantiles of daily total precipitation. There is statistically significant relationship between daily total precipitation, orography, and forest cover fraction on the territory.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"41 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3103/s1068373924050078
K. Saplioglu, T. S. Kucukerdem Ozturk
Abstract
Missing data in water resources studies prevent planning. For this reason, data estimation studies are carried out. In this study, ANFIS (Adaptive Neural Fuzzy Inference System) was used to complete the missing data. At the study area, the Yesilirmak Basin located in the north of Turkey, input variables from seven stations and output variable from one station were determined. In the research, 80% (378 months of data) of 504 months of the flow data between 1969 and 2011 was used in the training phase and 20% (126 months of data) was employed in the testing one. The decision tree was used instead of the trial and error method in the selection of input variables and determining the number of membership functions in ANFIS models. It was concluded that the ANFIS model established with the information obtained from the decision tree is successful compared to the randomly established ANFIS models. Using the decision tree before ANFIS models are created will not only minimize the time spent on the model development, but also prevent the best of the possible models from being overlooked.
{"title":"Effect of Decision Tree in the ANFIS Models: An Example of Completing Missing Data","authors":"K. Saplioglu, T. S. Kucukerdem Ozturk","doi":"10.3103/s1068373924050078","DOIUrl":"https://doi.org/10.3103/s1068373924050078","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Missing data in water resources studies prevent planning. For this reason, data estimation studies are carried out. In this study, ANFIS (Adaptive Neural Fuzzy Inference System) was used to complete the missing data. At the study area, the Yesilirmak Basin located in the north of Turkey, input variables from seven stations and output variable from one station were determined. In the research, 80% (378 months of data) of 504 months of the flow data between 1969 and 2011 was used in the training phase and 20% (126 months of data) was employed in the testing one. The decision tree was used instead of the trial and error method in the selection of input variables and determining the number of membership functions in ANFIS models. It was concluded that the ANFIS model established with the information obtained from the decision tree is successful compared to the randomly established ANFIS models. Using the decision tree before ANFIS models are created will not only minimize the time spent on the model development, but also prevent the best of the possible models from being overlooked.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"9 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-27DOI: 10.3103/s1068373924040071
A. E. Shishov
Abstract
Due to high spatial and temporal resolution, geostationary meteorological satellite imagery is a valuable source of information on the development of deep convective clouds and related severe weather events. Some methods for automatic deep convection detection from satellite data provide a satisfactory probability of detection for independent datasets, but are characterized by a high false alarm rate. The paper gives a description of an algorithm for automatic detection of deep convective clouds with satellite imagery using gradient boosting, logistic regression, and artificial neural network models. The results of validation of the proposed method using dependent and independent data of ground-based observations for the period 2013–2020 are presented. A low false alarm rate and high probability of detection suggest that the algorithm can be used in the operational mode.
{"title":"A Method for Object-oriented Detection of Deep Convection from Geostationary Satellite Imagery Using Machine Learning","authors":"A. E. Shishov","doi":"10.3103/s1068373924040071","DOIUrl":"https://doi.org/10.3103/s1068373924040071","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Due to high spatial and temporal resolution, geostationary meteorological satellite imagery is a valuable source of information on the development of deep convective clouds and related severe weather events. Some methods for automatic deep convection detection from satellite data provide a satisfactory probability of detection for independent datasets, but are characterized by a high false alarm rate. The paper gives a description of an algorithm for automatic detection of deep convective clouds with satellite imagery using gradient boosting, logistic regression, and artificial neural network models. The results of validation of the proposed method using dependent and independent data of ground-based observations for the period 2013–2020 are presented. A low false alarm rate and high probability of detection suggest that the algorithm can be used in the operational mode.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"70 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141523064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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