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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 159)
Nature Climate Change     Full-text available via subscription   (Followers: 151)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 80)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Climatic Change     Open Access   (Followers: 71)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Advances in Climate Change Research     Open Access   (Followers: 60)
Journal of Climate     Hybrid Journal   (Followers: 56)
Climate Policy     Hybrid Journal   (Followers: 53)
Climate Change Economics     Hybrid Journal   (Followers: 50)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 44)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
American Journal of Climate Change     Open Access   (Followers: 42)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 41)
Atmospheric Science Letters     Open Access   (Followers: 40)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Atmosphere     Open Access   (Followers: 33)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 32)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 30)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 29)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
Climate Change Responses     Open Access   (Followers: 27)
Space Weather     Full-text available via subscription   (Followers: 27)
Energy & Environment     Hybrid Journal   (Followers: 26)
Climate Resilience and Sustainability     Open Access   (Followers: 26)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
Journal of Climate Change     Full-text available via subscription   (Followers: 25)
Advances in Meteorology     Open Access   (Followers: 25)
International Journal of Environment and Climate Change     Open Access   (Followers: 24)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 24)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Current Climate Change Reports     Hybrid Journal   (Followers: 22)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 21)
Tellus A     Open Access   (Followers: 21)
Journal of Economic Literature     Hybrid Journal   (Followers: 20)
Tellus B     Open Access   (Followers: 20)
Global Meteorology     Open Access   (Followers: 19)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 19)
Weatherwise     Hybrid Journal   (Followers: 18)
Weather and Climate Extremes     Open Access   (Followers: 18)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Climate Risk Management     Open Access   (Followers: 12)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 12)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Climate Research     Hybrid Journal   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 8)
The Cryosphere (TC)     Open Access   (Followers: 8)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Climate of the Past (CP)     Open Access   (Followers: 7)
Climate     Open Access   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 7)
Climate Law     Hybrid Journal   (Followers: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Carbon Balance and Management     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 5)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Urban Climate     Hybrid Journal   (Followers: 5)
Meteorological Applications     Open Access   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Climate Services     Open Access   (Followers: 4)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Atmospheric Environment : X     Open Access   (Followers: 3)
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Oxford Open Climate Change     Open Access   (Followers: 3)
Environmental and Climate Technologies     Open Access   (Followers: 3)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Atmósfera     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 2)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Nīvār     Open Access   (Followers: 1)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Journal of Agricultural Meteorology     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  

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Journal Cover
Theoretical and Applied Climatology
Journal Prestige (SJR): 0.867
Citation Impact (citeScore): 2
Number of Followers: 14  
 
  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]
  • 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'

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      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: 2022-08-16
       
  • Observed features of monsoon low-level jet and its relationship with
           rainfall activity over a high-altitude site in Western Ghats, India

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      Abstract: Abstract In the present work, monsoon low-level jet (MLLJ) characteristics and its relationship with rainfall activity have been studied using three years (2016–2018) of radiosonde observations taken from a high altitude site (Mahabaleshwar, 1348 m AMSL) in Western Ghats, India. Initial analysis of zonal and meridional winds showed an apparent monthly variation with respect to altitude with robust features in zonal winds compared to meridional winds. Analyzed zonal wind and vertical shear in zonal wind during south west monsoon showed clear intra seasonal variation with respect to altitude especially below 5 km. Derived MLLJ characteristics, such as core speed, core height, and westerly wind depth, also exhibited apparent intra-seasonal variation where core height was comparatively invariant. Strong zonal wind and vertical shear in the zonal wind including higher core speed and westerly wind depth was noticed during July and August compared to June and September. Further, MLLJ association with rainfall activity has been analyzed. An increase in core speed and westerly wind depth was noted during the active period of monsoon compared to the break period. Later, the evolution of MLLJ characteristics before, during, and after heavy and high rainfall has been analyzed which showed strengthening of zonal wind, vertical shear in zonal wind, core speed, and westerly wind depth before and during the rainfall events categorized. Abundant moisture transport from the Arabian Sea to the Indian land mass prior to the event was noticed in the analysis of zonal water vapor flux. Intensification of few MLLJ characteristics mostly brings copious moisture, possibly leading to heavy or high rainfall over the study region.
      PubDate: 2022-08-16
       
  • Spatio-temporal distribution of atmospheric blocking events in the
           Northern and Southern Hemispheres

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      Abstract: Abstract The current research aims at studying the spatio-temporal distribution of blocking events in the Northern and Southern Hemispheres from 1968 to 2018, for a period of 51 years based on the Wiedenmann block intensity (BI) index. The results showed that blocking events in the Northern Hemisphere are almost twice as often as in the Southern Hemisphere. This could be due to the uneven distribution of land and water areas, and resulted from the greater temperature differences in the Northern Hemisphere. Blockings in the Northern Hemisphere are also stronger than in the Southern Hemisphere in terms of intensity, strength, and durability. The reason can be attributed to the greater temperature difference between water and land in the Northern Hemisphere. In terms of seasonal occurrence of blockings, the highest frequency of blockings in the Northern Hemisphere is related to spring in the North Atlantic and in the Southern Hemisphere, it is related to winter in the South Atlantic region. The growth trend of blockings in the Northern Hemisphere was faster by 54% and in the Southern Hemisphere by 26%. The results also showed that the core of the blockings in the Northern Hemisphere corresponds to the three troughs of the Northern Hemisphere, but the core of the blockings of the Southern Hemisphere is formed at the southernmost lands of the Southern Hemisphere, i.e., at the costal zones of the Southern Hemisphere continents where the temperature difference is maximum. These regions include the Philippine Archipelago, Indonesia, and Australia in the east of the Pacific Ocean, and the coasts of Chile and Peru in the west of the Pacific Ocean.
      PubDate: 2022-08-15
       
  • Reconstruction of a new ENSO prediction model by identifying causal
           factors based on an improved TriBA topological structure genetic algorithm
           

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      Abstract: Abstract To address the inaccuracy of long-term El Niño-Southern Oscillation (ENSO) predictions, a new ENSO dynamical-statistical prediction model is established based on the combination of model reconstruction and an improved TriBA parallel genetic algorithm. We also introduce the information flow method, which is used to clarify the cause-and-effect relationship between time series, to allow forecast factors to be found in a scientific manner and improve mid- and long-term forecast results. Using this ENSO index dynamical-statistical prediction model, sea surface temperature anomalies (SSTAs) in the equatorial eastern Pacific and El Niño and La Niña events are predicted. The results show that our model has good real-time prediction ability for up to a 14-month lead time. It is shown that the overall ENSO prediction ability of our model is very good across a 60-year period. Compared with six mature models, the root mean square error (RMSE) and the correlation of the improved model are slightly worse than those of the European Centre for Medium-Range Weather Forecasts (ECMWF) model but better than those of the other five models. In addition, the gap between the summer and winter prediction results is not large, which suggests that the “spring prediction barrier” can be overcome to a certain extent. Our model represents a new technique for the prediction and exploration of ENSO.
      PubDate: 2022-08-15
       
  • Temporal and spatial distribution characteristics of drought and flood
           considering the influence of underlying surface in Hainan Island, tropical
           areas of China

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      Abstract: Abstract Most studies of temporal and spatial distribution characteristics for droughts and floods analysis were conducted only from the perspective of a single factor (precipitation), while ignoring the impact of the underlying surface on the formation of droughts and floods. Based on the daily precipitation data of 88 meteorological stations in Hainan Island from 1970 to 2019, 30 m resolution DEM data and land use dataset, etc., the precipitation Z index was used to evaluate the level of drought and flood in Hainan Island. The analysis results were revised by underlying surface data to evaluate the spatiotemporal characteristics of the drought and flood areas. The drought- and flood-prone areas in Hainan Island were divided. The results show that the overall drought areas show an obvious downward trend, while the flood areas present an increasing trend. The drought-prone areas throughout the year are more concentrated in the northeast of Hainan Island, while the flood-prone areas are mainly distributed in the eastern coastal areas. The drought- and flood-prone areas before and after the revision by the underlying surface were compared. It can be seen that the overall trend is relatively similar and obvious before and after the revision. The drought- and flood-prone areas before revision are 7.97 and 2.91 times larger than that after revision, respectively. Finally, combining climate and underlying surface factors, suggestions for drought and flood prevention are put forward.
      PubDate: 2022-08-15
       
  • Spatio-temporal variability and trend analysis of rainfall in Wainganga
           river basin, Central India, and forecasting using state-space models

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      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: 2022-08-13
       
  • Post-processing of the UKMO ensemble precipitation product over various
           regions of Iran: integration of long short-term memory model with
           principal component analysis

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      Abstract: Abstract An accurate forecast of precipitation can significantly enhance the management of water resources. While the data originated from ground-based synoptic stations are known to be the most accurate inputs of hydrological models, it is mostly unavailable in developing countries. So, the other approaches, such as numerical weather predictions (NWPs), are considered proper alternatives. This study utilized the precipitation data of the UK Meteorological Office (UKMO) model over eight different regions of Iran. The eleven ensemble data of UKMO at 47 ground-based synoptic stations from 2007 and 2017 were chosen as the input variables, while the ground-based precipitation was considered the output variable. The long short-term memory (LSTM) model was used as the predictive model, and the three proposed input strategies were evaluated using correlation coefficient (CC) and normalized-root mean squared error (NRMSE). The results showed that the combination of LSTM and the principal component analysis (PCA) approaches in post-processing of the UKMO data (PPUKMOD) enhances CC and NRMSE by 9% compared to the raw UKMO dataset. Besides, the most performance in PPUKMOD is found in the G7 (Zagros Highlands) region. Moreover, the Zagros mountain and the northern-eastern part of Iran showed better performance in PPUKMOD based on the evaluation of longitude, latitude, and elevation ranges. The temporal assessment also revealed that the highest performance in PPUKMOD was observed in the cold and rainy months (CCaverage = 0.59 and NRMSEaverage = 0.74) where November was the first rank. The proposed methodology for post-processing the UKMO ensemble sources aligns well with Iran’s observed precipitations. Subsequently, it can be used as the input of hydrological models.
      PubDate: 2022-08-12
       
  • Modelling drought vulnerability tracts under changed climate scenario
           using fuzzy DEMATEL and GIS techniques

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      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: 2022-08-11
       
  • Assessment of paddy expansion impact on regional climate using WRF model:
           a case study in Sanjiang Plain, Northeast China

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      Abstract: Abstract Paddy expansion changes land use types and increases irrigation, which results in altering surface-atmosphere energy flux exchange processes with an additional impact of increase in temperature. The paddy fields have expanded approximately 14 times in the Sanjiang Plain since the 1990s. The main conversion sources for this expansion are dryland, wetland, and woodland. This expansion in paddy area induced by different sources has an integrated effect on regional climate that may produce warming or cooling effect, with different intensities in different zones. In this study, two numerical experiments (case A and case B) were designed to simulate the impacts of paddy expansion on temperature and energy flux by using the Weather Research and Forecasting (WRF) model. Irrigation cannot be ignored that it is considered a unique agricultural management measure for paddy field compared to other land covers. And considered to depict paddy expansion process accurately, multiple remote sensing-based vegetation indexes, such as green vegetation fraction (GVF) and surface albedo (ALB) were incorporated to specify the vegetation properties induced by paddy expansion. Hegang concentrated expansion zones (HGCE), Fuyuan concentrated expansion zones (FYCE), Tongjiang concentrated expansion zones (TJCE), and Sanjiang Plain expansion zones (SJPE) were selected for this research. The results revealed that paddy expansion decreased the near-surface temperature. Cumulative temperature declined by 0.80 °C (HGCE), 0.61 °C (FYCE), 0.69 °C (TJCE), and 0.43 °C (SJPE) from June to September with more significant near-surface cooling in summer (July and August). In terms of energy balance, an increase in latent heat (LH) and ground heat flux (G) and a decrease in sensible heat (SH) were observed, but the impact of paddy expansion was more significant on LH, followed by SH and G, respectively. This study provides valuable information for future agricultural activities adjustment and mitigating climate change at the regional scale.
      PubDate: 2022-08-11
       
  • Investigating the land surface albedo trend in Iran using remote sensing
           data

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      Abstract: Abstract The recent droughts in Iran have contributed to declining runoff, diminishing lake water levels, and rising salt levels due to lower runoff. This study aims to quantify how the recent changes affected to investigate the trend of land surface albedo in Iran between 2000 and 2018. Accessing field data from the Iran is difficult, and thus the common understanding of climate change in the region is strongly based on satellite data. We use remotely sensed data of land surface albedo, land surface temperature (LST), number of snow-covered days (SCDs), normalized difference vegetation index (NDVI), and the land cover type, obtained from Moderate Resolution Imaging Spectroradiometer (MODIS). The results show decreasing trends in albedo and SCDs by − 0.02 and − 0.52, respectively, and upward trends in the LST and NDVI data by 0.07 °C and 0.009, respectively. Due to the recent drought condition in Iran, SCDs decreased significantly, which might explain the reason behind the albedo decreases in winter time in Iran.
      PubDate: 2022-08-11
       
  • Weekend effect in summertime temperature and precipitation over the
           Yangtze River Delta region

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      Abstract: Abstract The Yangtze River Delta (YRD) region, located over East China, is an international urban agglomeration radiating Asia Pacific with convenient transportation, advanced manufacturing industry, and modern service industry. The intensive human activities have exerted substantial effects on the weather and climate over the YRD region during the past decades, thus bringing more challenges to accurate weather and climate forecasting. However, the weekly cycles of surface air temperature and precipitation linked closely to human activities and their corresponding physical processes remain insufficiently understood. Here, we investigate the weekly cycles of summertime surface air temperature and precipitation and the weekend effect over the YRD region for the period of 2008–2019 using high-resolution observational data and reanalysis data. The results demonstrate that lower surface air temperature and higher precipitation generally manifest during weekends compared to weekdays over the YRD region particularly over the areas with intensive human activities. Further analysis of the underlying physical processes points to the aerosol-cloud-radiation interaction which largely explains the weekend effect in summertime temperature and precipitation over the YRD region.
      PubDate: 2022-08-10
       
  • Bibliometric analysis of rice and climate change publications based on Web
           of Science

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      Abstract: Abstract To clarify the current situation, hotspots, and development trends in the field of rice and climate change topic research, a massive literature dataset were analyzed from the Web of Science database by bibliometric method. The research theme was chosen given the continuous increase of studies related to climatic changes and their consequences to rice. Based on the Web of Science core database, this study analyzed 4170 papers in the field of rice and climate change topic research from 1990 to July 2022, which include 86 highly cited papers and 3 hot papers. Papers were mainly written in English (4157, 99.688%), from 16,363 authors, 4017 organizations, and 129 countries/territories, published in 841 journals and seven book series. The top five Journals are Science of the Total Environment (136, 3.261%), Sustainability (89, 2.134%), Agronomy Basel (81, 1.942%), Agricultural and Forest Meteorology (77, 1.847%), and Climatic Change (74, 1.775%), each published more than 74 papers. Top five countries and regions of People’s Republic of China, the USA, India, Australia, and Japan were the major article contributors, each published more than 360 papers. Top five organizations of Chinese Acad Sci, Nanjing Agr Univ, Univ Chinese Acad Sci, Chinese Acad Agr Sci, and Int Rice Res Inst (IRRI) were popular based on contribution of articles more than 133 papers each. Among the all authors, top five authors were Tao Fulu, Pan Genxing, Zhang Zhao, Hasegawa Toshihiro, and Iizumi Toshichika, each published more than thirty papers. All keywords were separated into eight clusters for different research topics. Visualizations offer exploratory information on the current state in a scientific field or discipline as well as indicate possible developments in the future. The results will help researchers clarify the current situation in rice and climate change adaptation science but also provide guidance for future research. This work is also useful for student identifying graduate schools and researchers selecting journals.
      PubDate: 2022-08-10
       
  • Spatio-temporal evaluation of remote sensing rainfall data of TRMM
           satellite over the Kingdom of Saudi Arabia

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      Abstract: Abstract Rainfall estimation is the most important parameter for many water resource simulations and practices; therefore, precise and long-term data are required for trustworthy precipitation depiction. Recent advancements in remote sensing applications enabled researchers to estimate rainfall with greater geographical and temporal precision. The goal of this study was to evaluate the performance of a climatological satellite, the Tropical Rainfall Measuring Mission (TRMM) in estimating rainfall, with ground-based gauge data for five years (2008–2012) across the entire Kingdom of Saudi Arabia (KSA). In regional and station-based evaluations, many statistical performance metrics such as R-square (R2), root-mean-squared error (RMSE), mean absolute error (MAE), relative BIAS (R.B.), and correlation coefficient (CC) have been utilized. The southern, north-western, and south-western areas performed very well in the regression and correlation analyses. The problem of under and overestimating satellite data, according to R.B. analysis, exists across the Kingdom, with the southern, eastern, and north-western areas dominating (maximum over is R.B. = 94.6% and minimum over is 7.5%, while maximum under R.B. =  − 52.8% and minimum under R.B. =  − 5.9%). The RMSE and MAE were higher in the Qassim, Jazan, and Makkah regions, whereas they were the lowest in the northwestern. In general, TRMM prominently identified rainfall in comparison with the ground-based data and performed moderately for the majority of stations and regions during the research period.
      PubDate: 2022-08-10
       
  • Assessing and forecasting of groundwater level fluctuation in Joypurhat
           

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      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: 2022-08-09
       
  • Climate change impacts on reference evapotranspiration in South Korea over
           the recent 100 years

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      Abstract: Abstract The damage owing to climate change is increasing worldwide. In South Korea, the increase in temperature has exceeded the average global temperature increase. These temperature changes have increased the frequency and damage of droughts. To reduce drought damage, the importance of efficient water management policies and evapotranspiration (an index used for water management policies) is increasing. Generally, the potential evapotranspiration ( \({ET}_{0}\) ) is estimated by using the FAO-56 Penman–Monteith (PM) equation on meteorological datasets. In this study, long-term meteorological data with a maximum of 100 years were collected from 12 sites to estimate evapotranspiration. The objectives of this study were to (1) estimate the evapotranspiration based on the PM equation, (2) analyze the trends in the temperature and evapotranspiration, and (3) evaluate the relationship between the temperature and evapotranspiration through a correlational analysis. The results improve our understanding of climate change and provide a valuable reference for regional water resource management. It is found that there are generally increasing trends in spring, summer, and autumn, and generally decreasing trends in winter. The results from a seasonal Mann–Kendall test between the temperature and \({ET}_{0}\) show that the maximum temperature exhibits a distinct increase in spring and winter in certain areas. We determined the strengths of the relationships between temperature metrics and \({ET}_{0}\) using Pearson’s correlation coefficient, and the results show that the maximum temperature metric has the strongest relationship.
      PubDate: 2022-08-09
       
  • Investigating and predicting spatiotemporal variations in vegetation cover
           in transitional climate zone: a case study of Gansu (China)

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      Abstract: Abstract Vegetation ecosystems are sensitive to large-scale climate variability in climate transition zones. As a representative transitional climate zone in Northwest China, Gansu is characterized by a sharp climate and vegetation gradient. In this study, the spatiotemporal variations of vegetation over Gansu are characterized using the satellite-based normalized difference vegetation index (NDVI) observations during 2000–2020. Results demonstrate that a significant greening trend in vegetation over Gansu is positively linked with large-scale climate factors through modulating the water and energy dynamics. As a climate transition zone, the northern water-limited and southern energy-limited regions of Gansu are affected by water and energy dynamics, differently. In the water-limited region, a weakening Asian monsoon along with colder Central Pacific (CP) and warmer North Pacific (NP) Oceans enhances prevailing westerlies which bring more atmospheric moisture. The enhanced atmospheric moisture and rising temperature promote the local vegetation growth. In contrast, large-scale climate variations suppress the southwest monsoon moisture fluxes and reduce precipitation in southern energy-limited regions. In these energy-limited regions, temperature has more effects on vegetation growth than precipitation. Therefore, the greenness of vegetation is because of more available energy from higher temperatures despite overall drying conditions in the region. Based on the above mechanism, future scenarios for climate impacts on vegetation cover over Gansu region are developed based on the two latest generation from coupled climate models (Coupled Model Intercomparison Project Phase 5 and Phase 6; CMIP5 and CMIP6). In the near-term future (2021–2039), the vegetation is likely to increase due to rising temperature. However, the vegetation is expected to decrease in a long-term future (2080–2099) when the energy-limited regions become water-limited due to increasing regional temperatures and lowering atmospheric moisture flux. This study reveals an increasing desertification risk over Gansu. Similar investigations will be valuable in climate transition regions worldwide to explore how large-scale climate variability affects local ecological services under different future climate scenarios.
      PubDate: 2022-08-06
       
  • Annual and seasonal rainfall trend analysis using gridded dataset in the
           Wabe Shebele River Basin, Ethiopia

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      Abstract: Abstract Long-term rainfall trends analysis under climate change, particularly in developing countries where rainfed agriculture is substantial, is vigorous to evaluate rainfall variability brought changes and propose possible adaptation measures. Hence, the study was designed to evaluate annual and seasonal long-term trends in rainfall in Wabe Shebele River Basin in Ethiopia using gridded monthly precipitation data derived from Climate Research Unit (CRU TS 4.1) with 0.5° × 0.5° resolution from 1920 to 2019 years. The time series trend of annual and seasonal rainfall was detected by employing innovative trend analysis (ITA). The results were compared with the most widely used Mann–Kendall (MK) test and Sen’s slope estimator method. The basin was sub-divided into ten sub-basins for easy analysis. The MK test result revealed a non-significant decrease in annual and seasonal rainfall trends that occurred in most sub-basins and the entire basin. The results of the ITA method showed that the scattered plot was accumulated on the 1:1 (45°) straight line, indicating no trend for most of the sub-basins. The trends vary within sub-basins and rainfall magnitude while the decreasing and increasing trends were within ± 10%. The finding indicates that statistics for Φ are non-uniform spatial and temporal and show no significant trends at a 5% significant level in the most sub-basins. The comparison of the three selected methods indicates that ITA performs better in trend investigation. Hence, the ITA method provides results in graphical form, which makes a straightforward interpretation of trends based on rainfall intensity. Rainfall trends investigation is vital for agricultural development where combining the possible adaptation measures to climate change is vigorous during water resources planning and development for agriculture. Accordingly, the strategic plan is recommended for the practical activity of agriculture by considering the decline and variability of rainfall patterns in the sub-basins particularly and in the basin generally.
      PubDate: 2022-08-06
       
  • Assessing agrometeorological drought trends in Iran during 1985–2018

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      Abstract: Abstract The present study aims to investigate Iran’s agrometeorological drought history and its properties using Multivariate Standardized Drought Index (MSDI). For this purpose, precipitation and soil moisture recorded at 99 synoptic stations in Iran during 1985 to 2018 were selected. Based on MSDI time series, drought properties including duration and severity were calculated and trend analysis was carried on using Trend Free Prewhitening Mann Kendall test. Also, the standard normal homogeneity test was applied to investigate chronological drought change-point detection. From agrometeorological perspective, results showed that longer and more severe droughts are more dominant in southern, southeastern, northeastern, and some western regions of the country. Trend analysis revealed that most study stations have rising frequency and significant drying trend especially in winter at central plateau and western regions. Also, we recognized two main periods 1991–2000 and 2006–2010 that many stations experienced change-point in their MSDI time series, mainly because of climatic and anthropogenic causes. Drought properties assessment shows 6 stations with serious upward trend in drought duration and severity in northeast and western regions. Sens’s Slope statistics in these stations was calculated around 1.5 degree per event for drought severity and 1 month per event for drought duration. It is also observed that the 75th quantile of drought severity for most parts of the country is between 13 and 18 and the 75th quantile for drought duration varies between 8 and 24 months in different regions. The probability analysis revealed that most stations have a ratio around 2–5 times increase in drought occurrence probability after change point, leading to longer and more severe droughts in these stations. The paper indicates a serious situation related to agrometeorological drought occurrence, persistence, and severity in Iran because of many climatic and anthropogenic factors over the last 30 years.
      PubDate: 2022-08-05
       
  • Regionalization of rainfall intensity–duration–frequency (IDF) curves
           with L-moments method using neural gas networks

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      Abstract: Abstract Floods are one of the most frequent and destructive natural events which lead to lots of human and financial losses with damage to the houses, farms, roads, and other buildings. Intensity–duration–frequency (IDF) curves are the main and practical tools that have been used for flood control studies, including the design of the water structures. In many cases, there is no measuring device at the desired place, or their information is not helpful if there is any available. In this case, it is not possible to extract these curves through conventional methods. Regionalizing the IDF curves is a method that has solved the issues mentioned in the common methods. In this research, the regionalized IDF curves are extracted in Khuzestan province, Iran using 21 rain gauge stations through L-moments and neural gas networks. Clustering is one of the most effective steps and a prerequisite for regional frequency analysis (RFA) that divides the region and existing stations into hydrologically homogenous regions. In this study, clustering is done using two new models named neural gas (NG) and growing neural gas (GNG) network. Comparing the regional IDF curves with at-site curves, it was found that neural gas network models had a more accurate performance and higher efficiency, so they had the lowest estimate error amount among other models. Also, due to the acceptable difference between regional and at-site curves, the efficiency of L-moments in RFA was evaluated as appropriate.
      PubDate: 2022-08-05
       
  • Hydrological drought dynamics and its teleconnections with large-scale
           climate indices in the Xijiang River basin, South China

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      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: 2022-08-04
       
 
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