Russian Meteorology and Hydrology最新文献

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Variation Patterns of CO2 and CH4 according to the Measurements in the Surface Atmosphere over Urban and Suburban Areas in 2021–2022 根据 2021-2022 年城市和郊区地表大气测量结果得出的二氧化碳和甲烷变化模式

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要根据 2021 年 9 月至 2022 年 8 月在叶卡捷琳堡和库洛夫卡天文台（KAO）同步测量的结果，分析了城市化和郊区环境地表大气中二氧化碳和甲烷浓度的变化规律和因素。平均而言，叶卡捷琳堡的二氧化碳最高含量（百万分之 443.2）高于库洛夫卡天文台的最高含量（百万分之 432.4），且在一月达到最高值。相反，叶卡捷琳堡市的最低二氧化碳浓度低于郊区（叶卡捷琳堡市 7 月份为 405.4 ppm，而卡奥州 9 月份为 412.7 ppm）。KAO暖季二氧化碳浓度升高的原因是夜间浓度非常高（高达 500 ppm），这在城市地表大气中没有观测到。至于 CH4，城市和高纬度地区的季节动态相似：1 月份达到最大值（2.154 和 2.076 ppm），6 月份达到最小值（1.998 和 1.971 ppm）。据评估，研究区域的相互影响程度为中等。研究结果可用于开发区域碳平衡评估技术，这也是乌拉尔地区碳超级站点计划的主要任务。

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引用次数: 0

Influence of External Parameters on Evapotranspiration in the INM RAS–MSU Land Surface Model 外部参数对 INM RAS-MSU 陆面模型蒸散量的影响

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要本文研究了 INM RAS-MSU 陆面模型中的蒸散量对经纬度网格单元中陆面等级权重和叶面积指数 LAI 变化的敏感性。结果表明，根据现代观测数据对上述参数值的改进可显著减少蒸散量的误差。分析采用了俄罗斯北欧中等规模（2-50×103 平方公里）流域地表 10 年（2002-2012 年）的年平均蒸散量总和。根据流域水平衡方程得出的蒸散量经验估算值计算了模型误差。作为中间工作，计算中使用的陆地蓄水量卫星数据的准确性通过与雪路勘测数据的比较进行了评估。

引用次数: 0

Forecast Modeling of Invasive and Climate-driven Scenarios of Pest Outbreaks 入侵和气候驱动的害虫爆发情景预测模型

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要自 20 世纪末以来，在北冰洋北部森林地区观察到的气候变化产生了扩大生物物种分布范围的影响。气候驱动的入侵过程在动态上各不相同。在某些情况下，不受欢迎的物种会大量爆发。除了气候因素外，生物环境的反应也是一个重要方面。需要采用特殊方法来预测可能导致极端变化的快速入侵。由于气候变暖和有利条件，害虫的繁殖潜力往往过大。侵略性入侵往往是一个振荡过程，当物种适应环境时，入侵就会转变，而当原生生物群适应新物种时，入侵就会消退。不仅是新害虫，普通害虫的主要天敌也会成为有害入侵者。入侵的计算情景模式是基于逻辑上可扩展的混合方程结构开发的，其中考虑到了延迟适应，这种延迟适应在入侵爆发发展过程中根据气候因素表现出来。这些情景模式表明，在一次入侵爆发后，会出现一系列活动逐渐减弱的峰值，这样就有可能对导致种群在低谷期后重复活动的因素进行评估，因为在低谷期，超级寄生虫的入侵被证明是至关重要的。

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引用次数: 0

A Physical Mechanism-based Scheme for Parameterizing the Fractional Vegetation Cover 基于物理机制的植被覆盖率参数化方案

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要叶面积指数（LAI）和植被覆盖率（FVC）是陆地-大气相互作用中非常重要的参数。本研究根据冠层空隙率、叶面积指数和太阳直接消光系数之间的关系，开发了一种非常简单但稳健的基于机制的方法来推导 FVC 数据。为进行验证，将 LAI 数据、基于 NDVI 的 FVC 数据和基于机制的 FVC 数据同化到城市土地综合模型（IUM）中。与使用基于 NDVI 的 FVC 数据作为输入相比，使用基于机制的 FVC 数据作为输入，对北京地区年平均地表温度（LSTs）的模拟得到了改善。

引用次数: 0

Light Climate in Moscow 莫斯科的光照气候

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要根据莫斯科国立大学气象观测站对地球表面自然照度、不同方向垂直表面的照度以及影响其变化的因素进行的长期观测，介绍了莫斯科的光照气候。在大多数情况下，所获得的正常值足以满足任何实际应用的需要。研究中分析的一个问题是导致照度下降到临界值以下的条件，为此需要对房舍进行联合照明或人工照明。研究表明，照度可以根据一般天气预报预测的低空云层进行预报。

引用次数: 0

Spatiotemporal Changes in Cyclogenesis and Precipitation Regime over the Euro-Atlantic Sector in 1979–2019 1979-2019年欧洲-大西洋地区气旋生成和降水制度的时空变化

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要本研究根据欧洲-大西洋区域气旋的起源区域和路径对气旋进行了分类。气旋是根据ERA5再分析数据确定的。对气旋的季节频率、移动速度、大小和中心气压进行了量化，并揭示了其发展趋势。确定了与欧洲境内不同类型气旋相关的平均和最大总降水量。结果表明，近 40 年来，北大西洋气旋的频率在冬季、夏季和秋季有所下降，而在春季有所上升。研究还发现，南部气旋的频率在夏季明显减少，而在冬季增加。北大西洋某些类型气旋的最低中心气压在冬季和夏季有所下降。北大西洋气旋导致冬季最大降水总量增加，而南方气旋导致夏季最大降水总量增加。所有类型气旋的气旋降水日数都会减少。

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引用次数: 0

Statistical Correction of the SL-AV Model Long-term Forecasts of Surface Air Temperature for the Territory of Northern Eurasia SL-AV 模型对欧亚大陆北部地区地表气温长期预测的统计修正

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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。

引用次数: 0

Analysis of Average Daily Temperature and Precipitation on the Territory of Belarus Using Quantile Regression 利用定量回归分析白俄罗斯境内的日平均气温和降水量

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要采用量值回归法分析了日平均气温和日总降水量。考虑了与所选极端值（即低于 0.1（仅用于气温分析）和高于 0.9）相对应的量值。结果表明，在大多数情况下，冬季和夏季气温量值的空间分布接近平均值。气温和总降水量的时间变化特征与现代气候变暖相一致。只有当定量为 0.9 及以上时，气温与地球表面特征之间才存在统计意义上的显著关系。由于形成高强度降水的因素复杂，日总降水量的空间分布没有明显的规律。据统计，日总降水量、地形和境内森林覆盖率之间存在显著关系。

引用次数: 0

Effect of Decision Tree in the ANFIS Models: An Example of Completing Missing Data 决策树在 ANFIS 模型中的作用：缺失数据补全实例

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-07-26 DOI: 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.

摘要水资源研究中的数据缺失会妨碍规划。为此，人们开展了数据估算研究。本研究采用 ANFIS（自适应神经模糊推理系统）来补全缺失数据。在研究区域，即位于土耳其北部的耶希尔马克盆地，确定了七个站点的输入变量和一个站点的输出变量。在研究中，1969 年至 2011 年期间 504 个月流量数据的 80%（378 个月数据）用于训练阶段，20%（126 个月数据）用于测试阶段。在选择输入变量和确定 ANFIS 模型的成员函数数量时，使用了决策树而不是试错法。结论是，与随机建立的 ANFIS 模型相比，利用决策树获得的信息建立的 ANFIS 模型是成功的。在建立 ANFIS 模型之前使用决策树不仅能最大限度地减少模型开发所花费的时间，还能避免忽略可能的最佳模型。

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引用次数: 0

A Method for Object-oriented Detection of Deep Convection from Geostationary Satellite Imagery Using Machine Learning 利用机器学习从地球静止卫星图像中探测面向对象的深对流的方法

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Russian Meteorology and Hydrology

Pub Date : 2024-06-27 DOI: 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.

摘要由于具有高空间和时间分辨率，地球静止气象卫星图像是有关深对流云发展和相关恶劣天气事件的宝贵信息来源。从卫星数据中自动检测深对流的一些方法可为独立数据集提供令人满意的检测概率，但具有误报率高的特点。本文介绍了一种利用梯度提升、逻辑回归和人工神经网络模型对卫星图像中的深对流云进行自动检测的算法。文中介绍了使用 2013-2020 年期间地面观测的从属和独立数据对所提方法进行验证的结果。低误报率和高检测概率表明该算法可用于业务模式。

引用次数: 0

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