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  Subjects -> METEOROLOGY (Total: 112 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 198)
Nature Climate Change     Full-text available via subscription   (Followers: 133)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 80)
Atmospheric Environment     Hybrid Journal   (Followers: 73)
Atmospheric Research     Hybrid Journal   (Followers: 69)
Climatic Change     Open Access   (Followers: 64)
Journal of Climate     Hybrid Journal   (Followers: 54)
Bulletin of the American Meteorological Society     Open Access   (Followers: 51)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 48)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 43)
Climate Policy     Hybrid Journal   (Followers: 42)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 37)
Atmospheric Science Letters     Open Access   (Followers: 36)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 35)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 34)
Monthly Weather Review     Hybrid Journal   (Followers: 34)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 31)
American Journal of Climate Change     Open Access   (Followers: 29)
Advances in Climate Change Research     Open Access   (Followers: 29)
Journal of Hydrology and Meteorology     Open Access   (Followers: 29)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 28)
Weather and Forecasting     Hybrid Journal   (Followers: 28)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 27)
Journal of Space Weather and Space Climate     Open Access   (Followers: 27)
Atmosphere     Open Access   (Followers: 26)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 26)
Space Weather     Full-text available via subscription   (Followers: 25)
Advances in Meteorology     Open Access   (Followers: 24)
Energy & Environment     Hybrid Journal   (Followers: 24)
Tellus A     Open Access   (Followers: 22)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 21)
International Journal of Atmospheric Sciences     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 21)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 20)
Climate Change Economics     Hybrid Journal   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weather     Hybrid Journal   (Followers: 19)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 18)
Global Meteorology     Open Access   (Followers: 17)
Weather and Climate Extremes     Open Access   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 15)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 14)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Climate Change Responses     Open Access   (Followers: 10)
Climate Resilience and Sustainability     Open Access   (Followers: 9)
Climate law     Hybrid Journal   (Followers: 8)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 7)
Climate Change Research Letters     Open Access   (Followers: 7)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 7)
Climate     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 6)
Mathematics of Climate and Weather Forecasting     Open Access   (Followers: 6)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Climate Research     Hybrid Journal   (Followers: 6)
Current Climate Change Reports     Hybrid Journal   (Followers: 6)
Aeolian Research     Hybrid Journal   (Followers: 6)
The Cryosphere (TC)     Open Access   (Followers: 5)
Climate Risk Management     Open Access   (Followers: 5)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Climate of the Past (CP)     Open Access   (Followers: 5)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 5)
Urban Climate     Hybrid Journal   (Followers: 4)
International Journal of Environment and Climate Change     Open Access   (Followers: 4)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Carbon Balance and Management     Open Access   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
The Cryosphere Discussions (TCD)     Open Access   (Followers: 4)
Weatherwise     Hybrid Journal   (Followers: 4)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Climate Services     Open Access   (Followers: 3)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
Atmósfera     Open Access   (Followers: 3)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Journal of Climatology     Open Access   (Followers: 3)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Frontiers in Climate     Open Access   (Followers: 3)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 3)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3)
Atmospheric Environment : X     Open Access   (Followers: 3)
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Open Atmospheric Science Journal     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Journal of Climate Change     Full-text available via subscription   (Followers: 2)
Climate and Energy     Full-text available via subscription   (Followers: 2)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
气候与环境研究     Full-text available via subscription   (Followers: 1)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Mediterranean Marine Science     Open Access   (Followers: 1)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Weather and Climate Dynamics     Open Access  
Journal of Agricultural Meteorology     Open Access  
Nīvār     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Climate of the Past Discussions (CPD)     Open Access  
Revista Brasileira de Meteorologia     Open Access  
Studia Geophysica et Geodaetica     Hybrid Journal  

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Similar Journals
Journal Cover
Bulletin of Atmospheric Science and Technology
Number of Followers: 1  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2662-1495 - ISSN (Online) 2662-1509
Published by Springer-Verlag Homepage  [2653 journals]
  • Short-term forecasting of wind speed using time division ensemble of
           hierarchical deep neural networks
    • Abstract: Wind power in tropical countries like India has great potential as a major source of green energy. However, in order to do proper energy provisioning, there is a need to forecast and estimate the wind speed at windmill locations with an actionable lead-time. Forecasting wind speed at station level is a big challenge using dynamical models as it gives only macro level information. Therefore, use of statistical models is preferably adopted for this purpose. With the recent phenomenal growth of applications in artificial intelligence (AI), it is also possible to use data-driven models based on AI, especially deep learning for short-term forecasting of wind speed. In this paper, we have proposed a novel ensemble forecasting methodology using the long short-term memory (LSTM) model, which is a deep learning approach for time series data analysis. The capability of this approach has been demonstrated using wind speed data obtained from two meteorological stations located at New Delhi in North India and at Bengaluru in South India. We have used the ensemble methodology in two different modes; one is the averaging pooling and other is by using a hierarchical LSTM. The simulations using these models have been validated against the true observations at station scale. The ensemble forecasting method has shown promising results for 3-h early wind speed prediction at both the locations. The results are also compared with two classical statistical methods namely autoregressive and persistence models and two state-of-the-art data-driven models namely support vector machine (SVM) and extreme learning machine (ELM). The capability of the proposed method is demonstrated through various error matrices and found to have better performance. We believe that the proposed method has the potential to improve the short-term wind speed prediction capability at station level.
      PubDate: 2020-03-04
      DOI: 10.1007/s42865-020-00009-2
       
  • Barrier winds in the Italian region and effects of moist processes
    • Abstract: Barrier winds form when a sufficiently high mountain range causes a stratified airflow directed towards the orographic barrier to slow down at the low levels, producing a pressure imbalance, which in turn generates a mountain-parallel wind. The present study analyses barrier wind occurrence in the Italian region and surrounding seas from both a climatological and dynamical perspective. The main goals are to assess the applicability of the linear theory of upstream blocking to real-world cases and to investigate the role of atmospheric moist processes in promoting the formation and influencing the evolution of barrier winds. A 2-year climatology of barrier winds reveals that they occur more frequently than the opposite regime of flow over the orography, especially in the cold season. Barrier wind events are found to be associated with an upstream flow having a significantly higher inverse Froude number (or non-dimensional mountain height) values than flow-over events on average, consistently with the theory. An Alpine case study is simulated using numerical models and sensitivity tests are performed to investigate the dependence of barrier wind development and properties on the non-dimensional mountain height. Simulations reveal the strong influence of precipitation-related diabatic processes on the development of an upstream cold pool, which in turn supports barrier wind maintenance and strengthens its intensity. Idealized numerical experiments with varying upstream flow moisture shed light on processes leading to significant strengthening of barrier wind intensity, in particular on the crucial role of latent heat exchanges associated with precipitation.
      PubDate: 2020-02-28
      DOI: 10.1007/s42865-020-00005-6
       
  • Towards the profiling of the atmospheric boundary layer at European
           scale—introducing the COST Action PROBE
    • Abstract: The atmospheric boundary layer (ABL) is the layer closest to the Earth’s surface within which most human activities take place. The vertical profile of atmospheric thermodynamic parameters in the ABL impact weather, air quality and climate. However, surface sensor networks and satellite observations do not provide sufficient information on the high temporal variability and strong vertical gradients that occur in the ABL. Thus, the ABL represents an important but rather under-sampled part of the atmosphere. This observational gap currently hampers progress in numerical weather prediction, air quality forecasting and climate assessment. Due to recent technological and methodological advances, ground-based remote sensing instruments are now able to provide high-quality profiles of ABL parameters such as temperature, humidity, wind, aerosol and cloud properties. However, even though state-of-the-art ABL profilers are deployed at numerous sites in Europe, efficient science and technology networking and coordination is still required to exploit this rich dataset effectively. The current lack of data and procedure harmonization often diminishes the potential societal benefits of the existing ABL profiling data. This paper introduces PROBE, a new initiative funded by the European Cooperation in Science and Technology (COST), that aims to broaden the bridge between a wide range of user needs and the science and technology expertise residing in industry and academia, while strengthening and harmonizing methods and procedures to yield higher quality ABL observational data. Here, the challenges, objectives and implementation plan for PROBE are described, highlighting some preliminary results that will be further developed into operational applications during the 4-year duration (2019–2023) of this collaborative project.
      PubDate: 2020-02-26
      DOI: 10.1007/s42865-020-00003-8
       
  • Multifractal Characteristics of Cloud-to-Ground Lightning Intensity
           Observed in AMMA-CATCH Station (Northern Benin)
    • Abstract: Cloud-to-Ground (CG) lightning intensity time series recorded in northern Benin, during days of monsoon season (summer 2006), has been deeply explored using multifractal framework. The results suggest the existence of strong multifractal characteristics in lightning intensity. However, detrending the data reduces the degree of multifractality. The multifractality arises from both a fat-tailed probability density function and long-range temporal correlations. But, the most dominant multifractality in lightning intensity series depends strongly on the kind of detrending that is retained from the profile during the multifractal detrended fluctuation analysis (MFDFA). These findings have allowed us to understand and characterize the complexity of lightning intensity structure in the network.
      PubDate: 2020-02-18
      DOI: 10.1007/s42865-020-00004-7
       
  • Wind speed interpolation for evapotranspiration assessment in complex
           topography area
    • Abstract: Wind speed and direction are fundamental data for many application fields, such as power generation and hydrological modelling. Wind measurements are usually few and sparse; hence, spatial interpolation of wind data is required. However, in mountainous areas with complex orography, accurate interpolation of wind data should consider topographic effects. Due to computational constraints, fully physically based methods that solve thermodynamic and mass conservation equations in three dimensions cannot be applied for long-time simulations or very large areas, while fast empirical methods seem more suitable. The aim of this work is to compare fast empirical methods to interpolate wind speed against a physically based full atmospheric model in order to assess the impact of the introduced approximation in estimating the wind field and the potential evapotranspiration. Comparison is carried out over the area of the upper Po River basin, a predominantly alpine region located in northern Italy. Results show that empirical topographic correction can increase accuracy of interpolated wind speed in areas with complex topography, but it requires about 50% more computational time than simpler empirical methods that do not consider topography.
      PubDate: 2020-02-10
      DOI: 10.1007/s42865-019-00001-5
       
 
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