A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

              [Sort by number of followers]   [Restore default list]

  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted alphabetically
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 42)
Advances in Climate Change Research     Open Access   (Followers: 59)
Advances in Meteorology     Open Access   (Followers: 23)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 11)
Aeolian Research     Hybrid Journal   (Followers: 7)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
American Journal of Climate Change     Open Access   (Followers: 41)
Atmósfera     Open Access   (Followers: 2)
Atmosphere     Open Access   (Followers: 33)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 15)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 9)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 14)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 71)
Atmospheric Science Letters     Open Access   (Followers: 39)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 29)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Bulletin of the American Meteorological Society     Open Access   (Followers: 62)
Carbon Balance and Management     Open Access   (Followers: 6)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate     Open Access   (Followers: 6)
Climate and Energy     Full-text available via subscription   (Followers: 7)
Climate Change Economics     Hybrid Journal   (Followers: 50)
Climate Change Responses     Open Access   (Followers: 27)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Climate Law     Hybrid Journal   (Followers: 7)
Climate of the Past (CP)     Open Access   (Followers: 7)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Climate Policy     Hybrid Journal   (Followers: 56)
Climate Research     Hybrid Journal   (Followers: 8)
Climate Resilience and Sustainability     Open Access   (Followers: 29)
Climate Risk Management     Open Access   (Followers: 12)
Climate Services     Open Access   (Followers: 4)
Climatic Change     Open Access   (Followers: 71)
Current Climate Change Reports     Hybrid Journal   (Followers: 22)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 18)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 17)
Energy & Environment     Hybrid Journal   (Followers: 26)
Environmental and Climate Technologies     Open Access   (Followers: 3)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 24)
Frontiers in Climate     Open Access   (Followers: 4)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 17)
International Journal of Atmospheric Sciences     Open Access   (Followers: 24)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 33)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
International Journal of Environment and Climate Change     Open Access   (Followers: 24)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 164)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Journal of Climate     Hybrid Journal   (Followers: 55)
Journal of Climate Change     Full-text available via subscription   (Followers: 25)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Journal of Climatology     Open Access   (Followers: 3)
Journal of Economic Literature     Hybrid Journal   (Followers: 19)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 9)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 3)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 19)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 79)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Journal of Weather Modification     Full-text available via subscription   (Followers: 3)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Open Access   (Followers: 4)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 28)
Mètode Science Studies Journal : Annual Review     Open Access  
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 14)
Monthly Weather Review     Hybrid Journal   (Followers: 29)
Nature Climate Change     Full-text available via subscription   (Followers: 153)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Nīvār     Open Access   (Followers: 1)
npj Climate and Atmospheric Science     Open Access   (Followers: 4)
Open Atmospheric Science Journal     Open Access   (Followers: 4)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Oxford Open Climate Change     Open Access   (Followers: 6)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Space Weather     Full-text available via subscription   (Followers: 27)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Tellus A     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 20)
The Cryosphere (TC)     Open Access   (Followers: 8)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 31)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Urban Climate     Hybrid Journal   (Followers: 4)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Weather and Climate Extremes     Open Access   (Followers: 17)
Weather and Forecasting     Hybrid Journal   (Followers: 42)
Weatherwise     Hybrid Journal   (Followers: 18)
气候与环境研究     Full-text available via subscription   (Followers: 2)

              [Sort by number of followers]   [Restore default list]

Similar Journals
Journal Cover
Theoretical and Applied Climatology
Journal Prestige (SJR): 0.867
Citation Impact (citeScore): 2
Number of Followers: 13  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1434-4483 - ISSN (Online) 0177-798X
Published by Springer-Verlag Homepage  [2469 journals]
  • Record-breaking flood over the Yangtze River in early summer 2020: role of
           the north Indian Ocean and north tropical Atlantic SST

    • Free pre-print version: Loading...

      Abstract: Abstract The Yangtze River valley (YRV) suffered an extreme flood in the early summer (June-July; JJ) 2020, contemporaneous with warm sea surface temperature (SST) over the north Indian Ocean (NIO) and the north tropical Atlantic (NTA) regions. It is suggested that the warm NIO condition played dominant role in the heavy rainfall in China. The present study confirmed the contribution of the NIO warming and examined the underly processes by conducting statistical analysis. There are two ways by which the NIO SSTAs can influence the flooding in JJ 2020 by reinforcing the anomalous western North Pacific anticyclone (WNPAC). One is through an anomalous Kelvin wave in lower level troposphere that propagates into western Pacific and induces suppressed convection. The other is through a reversed Walker circulation over the Indo-Pacific regions that causes divergent circulation in lower level troposphere around WNP. In addition, we show that the warm NTA SSTAs could also enhance WNPAC and YRV flood through an anomalous zonal vertical circulation, with anomalous ascending motion over the NTA region and anomalous descending motion over tropical central-eastern Pacific. The intensified WNPAC facilitated moisture flux transport to YRV through southwesterly anomalies and resulted in extreme flood over YRV in JJ 2020. This study suggests that the NIO and NTA SSTAs can cause extreme flood event in YRV independent of El Niño-Southern Oscillation (ENSO), which highlights the importance of considering SSTAs over the NIO and NTA regions when predicting extreme climate events in China besides ENSO.
      PubDate: 2022-10-03
       
  • Projection of the Indian Summer Monsoon onset using a regionally coupled
           atmosphere–ocean model

    • Free pre-print version: Loading...

      Abstract: Abstract To examine the present and future mean variability of the Indian Summer Monsoon onset over Kerala, a high-resolution regional atmosphere–ocean coupled model (ROM) is deployed over the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia region. The model demonstrated its performance in simulating the onset and accompanying dynamical and thermodynamical characteristics. The model has shown reasonable skill in simulating the climatological onset with a slight delay when compared to observation (IMD) and reanalysis (NCEP), by 1 day in hindcast simulation (driven by ERA-40) and 4 days in historical simulation (driven by a global model of CMIP5; MPI-ESM), indicating the model bias in historical simulation is attributed to the driven forcing of parent MPI-ESM. Despite having abrupt transitional onset nature, its variability reflects strong teleconnections with the different modes of climate variability, such as El-Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Additionally, the model’s simulated onset dates have strong teleconnections with large-scale forcing such as sea surface temperature (SST). Under intermediate emission scenarios (RCP 4.5), ROM simulations are explored to assess future mean onset characteristics with possible deviations. The analysis indicates no shift in the projected mean onset with respect to historical simulation. The projected onset dates showed sizeable variability linked with future SST warming, suggesting that future ENSO and IOD events will substantially influence onset characteristics.
      PubDate: 2022-10-03
       
  • Correction to: The Arctic sea ice‑cloud radiative negative feedback in
           the Barents and Kara Sea region

    • Free pre-print version: Loading...

      PubDate: 2022-10-01
       
  • Hydrological drought dynamics and its teleconnections with large-scale
           climate indices in the Xijiang River basin, South China

    • Free pre-print version: Loading...

      Abstract: Abstract Hydrological drought is a highly complex and extreme natural disaster, which has increased in deficit, areal extent, and frequency with the penetration of climate change impact. For better anticipating hydrological droughts, it is crucial to evaluate hydrological drought and its teleconnections with large-scale climate indices (LSCI) effectively. This study estimated the dynamics and patterns of hydrological drought in the near-real river networks by virtue of the standardized runoff index (SRI) based on VIC and large-scale routing model in the Xijiang River basin, and revealed their teleconnections with the climate indices. Results show that model simulation can reasonably reveal the hydrological drought evolutions in near-real river networks and effectively expose the drought downward spread along main channels. The drought spread distances in Hongshuihe and Yujiang Rivers are farther under the comprehensive influence of climate, topography, and watershed shape. Hydrological drought evolutions in the upper reaches are mainly manifested as three patterns, including S12 (simultaneous significant changes in drought intensity, concentration degree, and frequency), S7(simultaneous significant changes in drought intensity and frequency), and S1(single significant change in drought intensity). These drought dynamic patterns are majority affected by climate variation patterns M1 (warm and cold AMO), M3 (cold PDO), and M7 (warm AMO/AO). For decision-makers, this work is beneficial for understanding and anticipating hydrological droughts in the river networks, and further selecting management strategies for water resources.
      PubDate: 2022-10-01
       
  • Characteristics of compound low-temperature and limited-light events in
           southern China and their effects on greenhouse grown strawberry

    • Free pre-print version: Loading...

      Abstract: Abstract The environmental stress, pests and diseases are frequently occurred during production of facility agriculture in China. Among them, adverse meteorological conditions, such as low temperature and limited light, often co-occurred in greenhouses and brought great losses in southern China. Nevertheless, there is little knowledge about agrometeorological disasters in facility, especially for co-occurred climate extremes. Here, we applied machine learning methods to simulate long-term daily minimum temperature in plastic greenhouses, so as to assess the spatio-temporal characteristics of compound low-temperature and limited-light events (LTLL) in southern China. We took strawberry as the representative horticulture plant to quantitatively investigate the potential effects of the LTLL stress based on experimental data. It was found that when the LTLL stress occurred, strawberry was more sensitive to low-temperature than limited-light and duration. The losses of the fruit soluble solids content caused by LTLL stress were relatively lower than that of yield. The LTLL events mainly occurred from November to March of the following year in southern China. The occurrence frequency had a decreasing trend during 1990–2019 at 3.4 d/10 a, which mainly resulted from its reduction in spring. Assuming that all the LTLL events occurred at strawberry flowering stage, ~ 11.71% of them could result strawberry fruit yield losses over 70%, and the most serious LL events mainly occurred in December and January. The northern part of southern China had a higher LTLL risk. The results have the potential to provide guidance for plastic greenhouse layout and strawberry production.
      PubDate: 2022-10-01
       
  • Assessing and forecasting of groundwater level fluctuation in Joypurhat
           

    • Free pre-print version: Loading...

      Abstract: Abstract Groundwater resource plays a crucial role for agricultural crop production and socio-economic development in some parts of the world including Bangladesh. Joypurhat district, the northwest part of Bangladesh, a crop production hub, is entirely dependent on groundwater irrigation. A precise assessment and prediction of groundwater level (GWL) can assist long-term groundwater resources (GWR) management, especially in drought-prone agricultural regions. Therefore, this study was carried out to identify trends and magnitude of GWL fluctuation (1980–2019) using the modified Mann–Kendall test, Pettitt’s test, and Sen slope estimators in the drought-prone Joypurhat district, northwest Bangladesh. Time-series data analysis was performed to forecast GWL from 2020 to 2050 using the Auto-Regressive Integrated Moving Average (ARIMA) model. The findings of the MMK test revealed a significant declining trend of GWL, and the trend turning points were identified in the years 1991, 1993, 1997, and 2004, respectively. Results also indicate that the declining rate of GWL varied from 0.104 to 0.159 m/year and the average rate of GWL declination was 0.136 m/year during 1980–2019. The outcomes of wavelet spectrum analysis depicted two significant periods of the declining trend in Khetlal and Akkelpur upazilas. The results obtained from the optimal identified model ARIMA (2, 1, 0) indicate that GWL will decline at a depth of 13.76 m in 2050, and the average declination rate of GWL will be 0.143 m/year in the study area. The predicted results showed a similar declining tendency of GWL from 2020 to 2050, suggesting a disquieting condition, particularly for Khetlal upazila. This research would provide a practical approach for GWL assessment and prediction that could help decision-makers implement long-term GWR management in the study area.
      PubDate: 2022-10-01
       
  • Modelling drought vulnerability tracts under changed climate scenario
           using fuzzy DEMATEL and GIS techniques

    • Free pre-print version: Loading...

      Abstract: Abstract The present study identifies drought risk zones in a river basin by analysing Landsat images from three selected precipitation deficit years (2000, 2009 & 2018). A set of seven parameters including standard precipitation index (SPI), long-term temperature condition index (TCI), long-term vegetation condition index (VCI), vegetation health index (VHI), long-term soil moisture index (SMI), long-term soil adjusted vegetation index (SAVI) and long-term normalised difference water index (NDWI) has been assessed, and drought risk zones have been identified using the fuzzy DEMATEL model to classify the causative and effective groups better represented through the causal diagram. A summary of the results shows that VHI, SPI, and TCI are the three most influential indicators of drought. A yield anomaly index (YAI) has been calculated for validation and the cropping pattern has been mapped.
      PubDate: 2022-10-01
       
  • Spatial distribution of the trends in potential evapotranspiration and its
           influencing climatic factors in Iraq

    • Free pre-print version: Loading...

      Abstract: Abstract Understanding the spatial variations in potential evapotranspiration (PET) and its influencing climatic variables is essential for sustainable agriculture and water resources management. However, little published research has investigated the alternation of PET due to climate change in the case of Iraq. The objective of the present study was to analyze the spatial trends in annual and seasonal PET in Iraq. Accordingly, the latest global ERA5-Land dataset of the European Centre for Medium-Range Weather Forecasts for 1981–2021 was employed. The PET was estimated using the FAO-Penman–Monteith method. The modified Mann–Kendall statistical test was applied to evaluate the significance of the trends in PET, which can separate unidirectional trends caused by climate change from the natural variability of climate. The attained results indicate that: (1) Over the past four decades, the annual and seasonal PET witnessed a significant increasing trend in almost all of Iraq, except for the alluvial plain in the eastern and southeastern parts. (2) The increasing trend in PET confirmed the patterns of the trend significance, with the highest increase of 0.28–0.65 mm/decade in southwest Iraq. (3) Summer had the highest upward trend of 0.35–0.65 mm/decade, followed by spring, autumn, and winter. (4) The air temperature was the predominant driving factor of rising PET, showing a positive correlation ranging from 0.77 to 0.88 and a contribution of 26 to 94%, mainly in the south, central, and northwest regions. The reverse contribution of wind speed and surface pressure to PET, particularly in the southeast and southwest, remains offset by the influence of air temperature and net solar radiation. Overall, the PET has risen drastically due to global climate change, indicating the potential for increased atmospheric water demand in the region.
      PubDate: 2022-10-01
       
  • The Arctic sea ice-cloud radiative negative feedback in the Barents and
           Kara Sea region

    • Free pre-print version: Loading...

      Abstract: Abstract Shortwave cloud radiative effect (SWCRE), known as the cooling effect triggered by cloud, plays a vital role in adjusting the global radiation budget. As the Arctic gets warmer, it may become a more indispensable factor curbing this warming tendency. Research has pointed out a significant relationship between sea ice cover (SIC) and SWCRE over the Arctic during summer (June–August). Although no evidence has been found on cloud response to SIC during summer on the average of the Arctic, this study regards cloud as an inter-connection which can regulate SIC and SWCRE in a particular place: Barents and Kara Sea region (15°E–85°E, 70°N–80°N). Its SWCRE and SIC vary significantly, with their trends being 5.85 w∙m−2 and − 5.87% per decade compared to those of the Arctic mean (2.93 w∙m−2 and − 4.65% per decade). In this area, we find that the growing number of low-level cloud which is resulted from the loss on SIC may be accountable for the increase in SWCRE, as is shown in the correlation coefficient between low-level cloud and SIC reaches − 0.4. The correlation coefficient between low-level cloud and SWCRE is 0.6. It reflects a SIC-cloud-SWCRE negative feedback. Moreover, a regression fitting model is being established to quantify the contribution of Arctic cloud in the process of slowing down the Arctic warming. It reveals that this specific region would turn into an ice-free region with sea surface temperature (SST) 1.5 °C higher than reality during 2001 if we stop the increase in SWCRE. This result presents how fascinating the contribution cloud has been making in its way slowing down the warming pace.
      PubDate: 2022-10-01
       
  • How rainfalls influence urban traffic congestion and its associated
           economic losses at present and in future: taking cities in the
           Beijing-Tianjin-Hebei region, China for example'

    • Free pre-print version: Loading...

      Abstract: Abstract Traffic congestion is one of serious problems in cities; rainfalls would exacerbate traffic congestion, and thus result in huge economic losses. However, limited studies focused on how rainfalls influenced traffic congestion and its associated economic losses. Based on detailed hourly data, we estimated how traffic congestion index (TCI) changed with different rainfall intensities in the Beijing-Tianjin-Hebei (BTH) region, and we also explored their economic losses. The results illustrated that all cities presented the similar trend of daily traffic congestion, and morning peak occurred 2 h later on holidays than workdays. Rainfall had significant impacts on traffic congestion for most time windows, except midnight. Traffic congestion increased with rainfall intensities, but smaller cities were more vulnerable to rainfall intensity than megacities. Rainfalls led to 0.95 billion yuan of extra economic losses in 2019, 38% of which occurred under heavy rainfalls. Traffic congestion in 2019 caused a total economic cost of 30.08 billion yuan in the BTH region (0.4% of its GDP), including the recurrent cost and economic losses due to rainfalls; besides, the social cost and direct cost contributed the same share of 49.5%, with 1% from the environmental costs. Considering future urban development and climate change, it is beneficial to establish the climate-resilient transportation system for avoiding future serious traffic congestion as well as huge economic losses in future.
      PubDate: 2022-10-01
       
  • What is above average air temperature!'

    • Free pre-print version: Loading...

      Abstract: Abstract In many media, especially in prime-time television shows, we often hear that the temperature is or will be higher than average or above average. It is seldom said which average it is, namely which period this comparison refers to. It is also rare to hear how much this above-average temperature is higher than one average. The question is what the climate average or climate normal is' The World Meteorological Organization (WMO) during the twentieth century defined a period of 30 years as the standard reference for calculating climate normal. The 30-year period, known as the climatological standard normal, serves as a benchmark against which current observations can be compared to the previous one. The last climatological standard normal period 1981–2010 is still in use while a new one is in preparation for a 30-year period that will cover the period from 1991 to 2020. It is expected that this change will be in use from the beginning of 2022. In this paper, based on the temperature change data obtained at the meteorological stations Split Marjan and Zagreb Grič, the differences in the conclusions about the last air temperature changes in the period of the last 10 years (2011–2020) are studied. The following four different 30-year climate normal periods are analysed: (1) 1961–1990; (2) 1971–2000; (3) 1981–2010; (4) 1991–2020. The analyses performed in this paper indicate the necessity of constant changing of the 30-year climate normal period used to estimate variations in recent air temperatures. Given the sudden rise in air temperature over the last 30 years, the period from 1991 to 2020 should be currently used for comparison and assessment of the most recent temperatures and other climatic parameters.
      PubDate: 2022-10-01
       
  • Dependence of spring Eurasian surface air temperature anomalies on the
           amplitude and polarity of the North Atlantic tripole SST anomalies

    • Free pre-print version: Loading...

      Abstract: Abstract This study compares boreal spring surface air temperature (SAT) anomalies over mid- and high-latitude Eurasia in different categories of the North Atlantic tripole sea surface temperature (SST) anomalies for the period 1951–2018. It is found that Eurasian SAT anomalies depend largely upon the amplitude and polarity of the North Atlantic tripole SST anomalies (positive polarity for positive SST anomalies in the tropics and mid-latitude and negative SST anomalies in the subtropics). The main processes contributing to SAT anomalies vary with the region. In large amplitude positive tripole years, the SAT decreases in Europe and east of the Lake Baikal due to longwave radiation and sensible heat flux and increases in Siberia due to horizontal advection associated with anomalous northerlies. In large amplitude negative tripole years, the SAT increases in Europe and eastern Eurasia due to horizontal advection associated with anomalous southerlies. In small amplitude positive tripole years, the SAT increases in central Eurasia due to horizontal advection associated with mean and anomalous meridional winds. In small amplitude negative tripole years, the SAT decreases in southern central Eurasia, which is contributed by both longwave radiation and horizontal advection associated with anomalous northeasterlies. Atmospheric circulation influences SAT both directly through horizontal advection associated with anomalous winds and indirectly through shortwave radiation and in turn upward longwave radiation and sensible heat flux. The results reveal the necessity of distinguishing the amplitude and polarity of the North Atlantic SST anomalies in their impacts on climate variability.
      PubDate: 2022-10-01
       
  • Improved complete ensemble empirical mode decompositions with adaptive
           noise of global, hemispherical and tropical temperature anomalies,
           1850–2021

    • Free pre-print version: Loading...

      Abstract: Abstract ICEEMDAN, a variant of Empirical Mode Decomposition (EMD), is used to extract temperature cycles with periods from half a year to multiple decades from the HadCRUT5 global temperature anomaly data. The residual indicates an overall warming trend. The analysis is repeated for the Southern and Northern Hemispheres as well as the Tropics, defined as areas lying at or below 30 degrees of latitude. Multiannual cycles explain the apparently anomalous pause in global warming starting around 2000. The previously identified multidecadal cycle is found to be the most energetic and to account for recent global warming acceleration, beginning around 1993. This cycle’s amplitude is found to be more variable than by previous work. Moreover, this variability varies by latitude. Sea ice loss acceleration is proposed as an explanation for global warming acceleration.
      PubDate: 2022-10-01
       
  • Spatio-temporal variability and trend analysis of rainfall in Wainganga
           river basin, Central India, and forecasting using state-space models

    • Free pre-print version: Loading...

      Abstract: Abstract Analysis of rainfall distribution and its changing pattern plays a vital role in managing water resources in a region. This work examined the spatio-temporal variability and trend of rainfall on yearly and season-wise scales during 1971–2013 in the Wainganga river basin situated in middle India. The Mann–Kendall (MK) test was implemented for identifying the temporal variation in rainfall trends. The magnitude of this changing trend was estimated by applying Sen’s slope (SS) method. A paired sample t-test was also employed to appraise the statistical significance of changes in rainfall data. The results of MK and SS tests show both upward and downward trends. The results show positive and negative trends in the south-eastern and northwestern parts of the study area for annual rainfall. The monsoon rainfall also shows very close proximity with annual rainfall data trends. The t-test states that the observed changes in precipitation are statistically significant. After trend and pattern analysis, state-space models (SSMs) were used to predict rainfall for future scenarios. Four SSMs (single, double, and triple exponential, autoregressive integrated moving average (ARIMA)) were employed for rainfall prediction. The analysis shows that the ARIMA is best for rainfall prediction with architecture of (0,0,0) (2,1,0) and can be used in Wainganga River basin.
      PubDate: 2022-10-01
       
  • Mapping the spatiotemporal diversity of precipitation in Iran using
           multiple statistical methods

    • Free pre-print version: Loading...

      Abstract: Abstract Despite being located in a semi-arid and arid part of the world, Iran enjoys a very diverse climate. Our objective is to regionalize the country into homogeneous precipitation regions and determine the monthly and annual precipitation water volume and depth in each region, required in hydro-climatological studies and applications, from simple water budget calculation to infrastructure design. We investigate the spatiotemporal diversity of precipitation over the country by analyzing the 33-year-long monthly precipitation time series (1983–2016) at 461 rain-gauge stations. We employed cluster analysis (CA) both hierarchical and non-hierarchical clustering approaches and principal component analysis (PCA) to determine the homogeneous precipitation zones at three macro-, meso-, and micro-scales (resolutions). First, the country is divided into six macro-precipitation regions (MPRs) using CA each showing a mean annual hyetograph of unique pattern and depth. The Siberian cold continental air mass enters the country from the north, the Sudan air mass from the south and southwest, the Mediterranean air mass from the west, the North Atlantic and the Black Sea cyclones from the northwest, and the Maritime air mass from the southeast create these six precipitation regions. Then, the six regions were divided into ten zones of meso-resolution through hierarchical clustering (HC) and k-means clustering. The occasional collision of the air masses causes the division of the six macro-regions into ten zones at meso-resolution. Finally, we subjected the precipitation time series of ten meso-zones to PCA, HC, and k-means clustering and established an optimal number of 24 micro-zones for the first time that reflects a comprehensive precipitation map over the country. The annual hyetograph of each zone shows a unique pattern and distribution with a varying magnitude of monthly precipitation compared to others as the result of varied physio-geographical characteristics of the country prevailing in each micro-zone. The result shows that hierarchical clustering (Ward’s method-Pearson correlation) and PCA have the same classification performance and strength in meso- and micro-climatological zoning. The long-term (i.e., 33 years) mean annual hyetograph in each region and zone is also calculated, and the monthly and annual-precipitation water volume and depth in the country are estimated. The findings provide the researchers, practitioners, and decision-makers with an accurate baseline reference for future research and water resource management and will advance the understanding of precipitation dynamics in different regions of the country.
      PubDate: 2022-09-13
       
  • Trend Slope Risk Charts (TSRC) for piecewise ITA method: an application in
           Oxford, 1771–2020

    • Free pre-print version: Loading...

      Abstract: Abstract In this study, the 250-year precipitation data, and the 200-year temperature data belonging to the Radcliffe station located in Oxford city of England have been analyzed. The piecewise trends, their magnitudes, and stabilities have been determined in the study through modified Mann–Kendall (m-MK), Sen’s slope (SS), and Innovative Trend Analysis (ITA) methodologies. This study is mainly proposed to suggest a new approach for the trend slope (magnitude) based on the ITA with Trend Slope Risk Charts (TSRC). The numerical evaluation of the trends obtained through the ITA graphs has been made for the first time via TSRC. The average trend magnitudes have been calculated for 50% risk level by forming the Cumulative Distribution Function (CDF) charts of the trend increase (or decrease) percentages to define the trend magnitudes over a single magnitude for the ITA methodology. The experts can find a chance with the TSRC to evaluate in detail the trend magnitudes for different numerical values. The m-MK methodology regarding total annual precipitation data emphasizes that there is no trend in general except for the three combinations. Nonetheless, there are trend increases in nine combinations, and partial trend decreases in two charts except for the 1871–1920 and 1971–2020 periods, according to the ITA methodology. On the other hand, the trend increases for five of the six combinations that are formed to determine the piecewise trends of the annual mean temperature data, and no trend evaluation for one of them is nearly similar for the m-MK and ITA methodologies. Finally, the differences between trend magnitudes are calculated through two different methodologies that have been discussed in detail within the scope of the study.
      PubDate: 2022-09-09
       
  • Modeling and forecasting of CO2 emissions resulting from air transport
           with genetic algorithms: the United Kingdom case

    • Free pre-print version: Loading...

      Abstract: Abstract The increase in the air transportation density affects global warming negatively by increasing the CO2 emitted to the environment. The issue becomes even more important when the agricultural lands and drinking water resources on the flight routes are considered. This situation leads to the development of certain environmental concerns in the society and makes it necessary for the countries to forecast in the correct direction to develop some preventive strategies. To make a contribution to this issue, emission modeling and forecasts regarding emissions originating from air transportation were made in this study through genetic algorithms, a popular artificial intelligence technique. Using the flight information of 32 European countries, the degree of relationship between the number of flights and passengers and CO2 emission from air transportation was calculated. Based on the highly correlating results obtained, time series models were developed for the UK’s domestic and international airline transportation in which the highest number of flights takes place and passengers are carried. Using these models, the forecasts based on the UK’s flight numbers until 2029, the number of passengers to be transported, and air transportation–related emissions were made. Results with high correlation values ranging from 0.99 to 0.87 were obtained in the implementations.
      PubDate: 2022-09-07
       
  • Correction to: Spatio-temporal variability and trend analysis of rainfall
           in Wainganga river basin, Central India, and forecasting using state-space
           models

    • Free pre-print version: Loading...

      PubDate: 2022-09-01
       
  • Contrasting features of monsoon convection over land and sea in the west
           coast of peninsular India as revealed by S-band radar

    • Free pre-print version: Loading...

      Abstract: Abstract Monsoon convection characteristics over land and sea within 150 km of the west coast of India are studied using coastal Mumbai S-band radar. The intraseasonal and interannual monsoon variabilities in cloud characteristics are investigated for the contrasting monsoon seasons of 2013 and 2014. The cloud characteristics studied are frequency of occurrences, cloud top height (CTH), longitudinal distribution, diurnal variation, and scale-wise distribution of cloud cells. The number of cloud cells is about four times higher over land than over sea. The maximum frequency of CTH is found in the cumulus category (3–4 km). The mean CTH varies from 4.49–5.44 km. No significant difference between the CTH over the land and sea regions is found. The contribution of congestus to total cloud cells is found maximum over both land and sea. The longitudinal variation of cloud frequency shows maximum frequency at a distance of 50–60 km from the location of radar over both sea and land. The maximum over the land region is the new feature revealed in the analysis. The diurnal variation of clouds shows a broad structure with maximum in the local noon and minimum in the morning hours. The mean duration of the clouds is 40–44 min both over land and sea. The contribution by the mesoscale convective system (MCS) is dominant (57–63%). The study of cloud distribution over land and sea over the west coast of India using radar data is the first of its kind and has brought out detailed structure of cloud distribution with time and space.
      PubDate: 2022-08-31
       
  • Daily average relative humidity forecasting with LSTM neural network and
           ANFIS approaches

    • Free pre-print version: Loading...

      Abstract: Abstract Because hurricanes, droughts, floods, and heat waves are all important factors in measuring environmental changes, they can all result from changes in atmospheric air temperature and relative humidity (RH). Besides, climate, weather, industry, human health, and plant growth are all affected by RH. Accurately and consistently forecasting RH is a challenge due to its non-linear nature. The present study tried to predict one day ahead of RH in determined provinces from different climatic regions of Turkey (Ankara, Erzurum, Samsun, Diyarbakır, Antalya, and Bilecik) using long short-term memory (LSTM) and adaptive neuro-fuzzy inference system (ANFIS) with fuzzy c-means (FCM)–based machine learning models. As evaluation criteria, root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (R) were employed. The outcomes from the forecasting models were also validated using observed data. During the testing stage, the smallest MAE and RMSE values were discovered to be 5.76% and 7.51%, respectively, in Erzurum province, with an R value of 0.892 when using the LSTM method. Moreover, the smallest MAE and RMSE values were obtained to be 5.95% and 7.67%, respectively, in Erzurum province with an R value of 0.887 using the ANFIS model according to the daily RH prediction. The results indicate that both the LSTM and ANFIS approaches performed satisfactory performance in daily RH prediction, with the LSTM and ANFIS approaches producing nearly identical results.
      PubDate: 2022-08-27
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 3.238.199.4
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-