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  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)

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Advances in Meteorology
Journal Prestige (SJR): 0.48
Citation Impact (citeScore): 1
Number of Followers: 23  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-9309 - ISSN (Online) 1687-9317
Published by Hindawi Homepage  [339 journals]
  • The Influence of Data Length on the Performance of Artificial Intelligence
           Models in Predicting Air Pollution

    • Abstract: Air pollution is one of humanity's most critical environmental issues and is considered contentious in several countries worldwide. As a result, accurate prediction is critical in human health management and government decision-making for environmental management. In this study, three artificial intelligence (AI) approaches, namely group method of data handling neural network (GMDHNN), extreme learning machine (ELM), and gradient boosting regression (GBR) tree, are used to predict the hourly concentration of PM2.5 over a Dorset station located in Canada. The investigation has been performed to quantify the effect of data length on the AI modeling performance. Accordingly, nine different ratios (50/50, 55/45, 60/40, 65/35, 70/30, 75/25, 80/20, 85/15, and 90/10) are employed to split the data into training and testing datasets for assessing the performance of applied models. The results showed that the data division significantly impacted the model's capacity, and the 60/40 ratio was found more suitable for developing predictive models. Furthermore, the results showed that the ELM model provides more precise predictions of PM2.5 concentrations than the other models. Also, a vital feature of the ELM model is its ability to adapt to the potential changes in training and testing data ratio. To summarize, the results reported in this study demonstrated an efficient method for selecting the optimal dataset ratios and the best AI model to predict properly which would be helpful in the design of an accurate model for solving different environmental issues.
      PubDate: Fri, 30 Sep 2022 11:05:02 +000
       
  • Spatio-Temporal Rainfall Variability and Concentration over Sri Lanka

    • Abstract: Changes in precipitation patterns significantly affect flood and drought hazard management and water resources at local to regional scales. Therefore, the main motivation behind this paper is to examine the spatial and temporal rainfall variability over Sri Lanka by Standardized Rainfall Anomaly Index (SRAI) and Precipitation Concentration Index (PCI) from 1990 to 2019. The Mann–Kendall (MK) trend test and Sen’s slope (SS) were utilized to assess the trend in the precipitation concentration based on PCI. The Inverse Distance Weighting (IDW) interpolation method was incorporated to measure spatial distribution. Precipitation variability analysis showed that seasonal variations are more than those of annual variations. In addition, wet, normal, and dry years were identified over Sri Lanka using SRAI. The maximum SRAI (2.27) was observed for the year 2014 for the last 30 years (1990–2019), which shows the extremely wet year of Sri Lanka. The annual and seasonal PCI analysis showed moderate to irregular rainfall distribution except for the Jaffna and Ratnapura areas (annual scale-positive changes in Katugastota for 21.39% and Wellawaya for 17.6%; seasonal scale-Vavuniya for 33.64%, Trincomalee for 31.26%, and Batticaloa for 18.79% in SWMS). The MK test, SS-test, and percent change analyses reveal that rainfall distribution and concentration change do not show a significant positive or negative change in rainfall pattern in Sri Lanka, despite a few areas which experienced significant positive changes. Therefore, this study suggests that the rainfall in Sri Lanka follows the normal trend of precipitation with variations observed both annually and seasonally.
      PubDate: Wed, 28 Sep 2022 11:05:03 +000
       
  • Blue-Green Space Changes of Baiyangdian Wetland in Xiong’an New
           Area, China

    • Abstract: As a regulator of ecological environment, Baiyangdian Wetland is in a pivotal position in constructing the blue-green space (BGS) of Xiong’an New Area in China. This study aims to reveal the spatiotemporal changes of the BGS in Baiyangdian Wetland from 2016 to 2021. It uses Google Earth Engine (GEE) to calculate NDVI and NDWI based on Sentinel-2 Satellite remote sensing data and extracts the blue-green space by a classification model driven by NDVI and NDWI. Moreover, the land-use transfer matrix and landscape pattern indices are applied for evaluating the BGS changes in the wetland. According to the results, vegetation in the wetland shows no obvious spatial transfer. From 2016 to 2020, the BGS proportion in the wetland showed a stable increase, with the blue space getting larger by 10.8%. The indicators of the Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI), Contagion, and Landscape Shape Index (LSI) of the wetland decreased, suggesting a better ecological environment since the establishment of Xiong’an New Area in 2017. Based on the results, the author makes the following conclusion: the construction of BGS in Baiyangdian Wetland results in a well-organized ecological environment. The study provides a reference for building Xiong’an New Area and monitoring BGS changes in other regions.
      PubDate: Tue, 27 Sep 2022 12:35:03 +000
       
  • The Space Conceptual Models and Water Vapor Characteristics of Typical
           Rainstorms during Plum Rain Season

    • Abstract: Based on conventional observation data from the China Meteorological Administration (CMA) and reanalysis data from the American National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) between 2012 and 2021, combined with the meteorological analysis, composite synthesis, and water vapor trajectory analysis, the weather circulations of typical rainstorms during the 10 years can be divided into 4 categories: Static Front Pattern (SFP), Subtropical High Edge Pattern (SHEP), Northeast Cold Vortex Pattern (NCVP), and Low-Level Vortex and Shear Pattern (LLVSP). The SHEP and SFP rainstorms have the characteristics of long duration and wide range, while the NCVP rainstorms are characterized by mobility and disaster weather accompaniment. The daily precipitation of LLVSP cases has extremity feature. The occurrence and development of rainstorms are well coordinated with the systems on lower levels. The main water vapor channel in lower layers of the SFP cases is from the South China Sea, while it is from Bohai for the NCVP cases and the Bay of Bengal for the SHEP and LLVSP cases. The main water vapor channel in middle layers is from the Bay of Bengal because of the affection of the southwest air flow. The south boundary of the MLYRB is the most important water vapor input boundary, followed by the west boundary, while the East and North boundaries are the outflow boundaries. During the rainstorms, the low-level water vapor is exuberant with low-level water vapor convergence much stronger than the high-level divergence. Among the four types of rainstorms, the NCVP cases provide the most abundant low-level water vapor convergence, resulting in the strongest short-term precipitation among the four types. Combined with water vapor transportation and convergence, the refined spatial conceptual models of the four types of rainstorms can better judge the process intensity and falling area and provide reference for disastrous weather forecast and early warning.
      PubDate: Mon, 26 Sep 2022 15:05:03 +000
       
  • Frost Forecasting considering Geographical Characteristics

    • Abstract: Regional accuracy was examined using extreme gradient boosting (XGBoost) to improve frost prediction accuracy, and accuracy differences by region were found. When the points were divided into two groups with weather variables, Group 1 had a coastal climate with a high minimum temperature, humidity, and wind speed and Group 2 exhibited relatively inland climate characteristics. We calculated the accuracy in the two groups and found that the precision and recall scores in coastal areas (Group 1) were significantly lower than those in the inland areas (Group 2). Geographic elements (distance from the nearest coast and height) were added as variables to improve accuracy. In addition, considering the continuity of frost occurrence, the method of reflecting the frost occurrence of the previous day as a variable and the synthetic minority oversampling technique (SMOTE) pretreatment were used to increase the learning ability.
      PubDate: Sun, 25 Sep 2022 17:35:02 +000
       
  • Variation in Surface Solar Radiation and the Influencing Factors in
           Xinjiang, Northwestern China

    • Abstract: The variation of solar radiation has a profound effect on the surface energy balance and hydrological cycle. Although the relationship between solar radiation variation and its influencing factors has been extensively studied, they are seldom used in Xinjiang, the largest province in China. In this study, we investigated the spatial distribution and temporal variation in global radiation (Eg), water vapor content (WVC), aerosol optical depth (AOD), total cloud cover (TCC), and low-level cloud cover (LCC) in Xinjiang, northwestern China, between 1961 and 2015. The annual average Eg reported at all stations was 5126.3–6252.8 MJ·m−2 with a mean of 5672 MJ·m−2. The highest annual mean Eg of 6252.8 MJ·m−2 occurred in Hami, eastern Xinjiang, whereas the lowest annual mean Eg of 5126.3 MJ·m−2 occurred in Urumqi, northern Xinjiang. The annual Eg variation was mainly affected by WVC, AOD, TCC, and LCC. Decreases in annual, spring, summer, autumn, and winter Eg trends were recorded in Xinjiang at rates of −33.88 × 10−2, −1.92 × 10−2, −1.89 × 10−2, −3.47 × 10−2, and −3.56 × 10−2 MJ·m−2·decade−1, respectively, with decreasing ratios of 9.43%, 5.85%, 0.14%, 8%, and 20.55%, respectively. Increasing trends in annual WVC, AOD, TCC, and LCC were noted in Xinjiang at rates of 7.12 × 10−5 mm·decade−1, 2.74 × 10−6 decade−1, 8.77 × 10−5 % decade−1, and 5.73 × 10−5% decade−1, respectively. In addition, increasing trends in the annual Eg at Yining and Yanqi stations were observed. The Eg spatial distribution was complex in Xinjiang at the stations observed in this study, which were divided into six groups. Eg at group 1 showed an increasing trend associated with decreases in the WVC and TCC, whereas decreases in Eg were observed at groups 2–6, which could have been influenced by increases in AOD, TCC, and LCC.
      PubDate: Mon, 12 Sep 2022 12:05:00 +000
       
  • Wavelet Analysis of the Interconnection between Atmospheric Aerosol Types
           and Direct Irradiation over Cameroon

    • Abstract: The comparative analysis of the intra- and interannual dynamics between the Direct Normal Irradiation (DNI) under clear sky conditions and five aerosol types (Dust, Sea Salt, Black Carbon, Organic Carbon, and Sulfate) is the purpose of this study. To achieve this aim, we used fifteen-year DNI and aerosols data downloaded at 3-hour time intervals in nine defined zones throughout Cameroon. The wavelet transform is a powerful tool for studying local variability of amplitudes in a temporal dataset and constitutes our principal tool. The results show unequal distribution of aerosol types according to zones, but the Desert Dusts (DU) and Organic Carbon (OM) aerosols have been found as dominant particles in the studied region. The wavelet coherence analysis between DNI and each aerosol type reveals three bands of periodicity: 4-month band, 8–16-month band, and sometimes after-32-month band, with the most important frequency at 8–16-month band period. However, the intensity of coherence across bands varies with respect to aerosol type as well as each of the nine climate zones. A significant anticorrelation relationship was obtained between DNI and each type of aerosol, emphasizing that the presence of such atmospheric particles could dampen the renewable energy utilized by power systems. Also, the analysis shows that scattering aerosols such as Sulfate and Sea Salt (SU and SS, respectively) lead DNI in phase while absorbing aerosols such as Organic Carbon, Black Carbon, and Dust (OM, BC, and DU, respectively) give phase lag with DNI.
      PubDate: Mon, 05 Sep 2022 23:50:01 +000
       
  • Data-Driven versus Köppen–Geiger Systems of Climate
           Classification

    • Abstract: Climate zone classification promotes our understanding of the climate and provides a framework for analyzing a range of environmental and socioeconomic data and phenomena. The Köppen–Geiger classification system is the most widely used climate classification scheme. In this study, we compared the climate zones objectively defined using data-driven methods with Köppen–Geiger rule-based classification. Cluster analysis was used to objectively delineate the world’s climatic regions. We applied three clustering algorithms—k-means, ISODATA, and unsupervised random forest classification—to a dataset comprising 10 climatic variables and elevation; we then compared the obtained results with those from the Köppen–Geiger classification system. Results from both the systems were similar for some climatic regions, especially extreme temperature ones such as the tropics, deserts, and polar regions. Data-driven classification identified novel climatic regions that the Köppen–Geiger classification could not. Refinements to the Köppen–Geiger classification, such as precipitation-based subdivisions to existing Köppen–Geiger climate classes like tropical rainforest (Af) and warm summer continental (Dfb), have been suggested based on clustering results. Climatic regions objectively defined by data-driven methods can further the current understanding of climate divisions. On the other hand, rule-based systems, such as the Köppen–Geiger classification, have an advantage in characterizing individual climates. In conclusion, these two approaches can complement each other to form a more objective climate classification system, wherein finer details can be provided by data-driven classification and supported by the intuitive structure of rule-based classification.
      PubDate: Wed, 31 Aug 2022 05:50:00 +000
       
  • Spatiotemporal Climate Variation and Analysis of Dry-Wet Trends for
           1960–2019 in Jiangsu Province, Southeastern China

    • Abstract: The spatiotemporal characteristics of dry-wet trends were identified and assessed, and the dominant meteorological factors were identified for the climate of Jiangsu province in humid southeastern China for the period 1960–2019. We conducted the research using data for the entire Jiangsu province as well as three major regions in Jiangsu (Huaibei, Jianghuai, and Sunan) with different regional climates. The results showed that decreased precipitation and relative humidity in spring and autumn over the study period were mainly responsible for the dry trends of the climates of all three regions and the entire province. Precipitation had a greater influence in spring and relative humidity in autumn. Decreases in sunshine hours and wind speed were responsible for the summer wet trends of the climates of Huaibei and Jianghuai and the entire province. However, precipitation increased significantly in the summer and was responsible for the increasing wet trend in Sunan. Significantly increased precipitation in winter was primarily responsible for the increasing wetness in Jianghuai and Sunan and the entire province in that season. However, the wet trend in northern Huaibei in winter was mainly caused by the decrease in wind speed over the study period. For the growing season and annually, the positive effects of changes in wind speed, sunshine hours, and precipitation led to increased humidity index in Jianghuai, Sunan, and the entire province. Precipitation showed a decreasing trend that countered the positive effects of decreases in wind speed and sunshine hours, which resulted in a slight decrease in the humidity index in Huaibei for both the growing season and annually. Sensitivity analysis indicated that the humidity index was positively sensitive to precipitation and relative humidity and negatively sensitive to air temperature, wind speed, and sunshine hours in Jiangsu province during 1960–2019. Overall, the humidity index in this region of southeastern China was most sensitive to changes in precipitation followed, in order of sensitivity, by sunshine hours, air temperature, wind speed, and relative humidity. Our findings provide a theoretical basis for adjusting irrigation programs and efficient utilization of water resources at the regional scale in humid southeastern China.
      PubDate: Sat, 27 Aug 2022 16:05:01 +000
       
  • Trend Analysis of Hydrometeorological Data of Gilgel Gibe Catchment,
           Ethiopia

    • Abstract: Trend analysis of hydrometeorological data is vital for proper water resources planning and management. This paper examines the trends of the hydrometeorological data in Gilgel Gibe catchment and whether the trends are significant. Daily rainfall, temperature, and streamflow data of the stations in/around (nearby) the catchment (7 stations for rainfall, 4 stations for temperatures, and 6 stations for streamflow) for a period longer than 25 years were collected and then analyzed to detect the variability and the changes in trend. Prior to conducting trend tests, the missed data were filled, and their inconsistencies were also adjusted. The nonparametric Mann-Kendall test along with Sen’s slope technique was employed to detect monotonic trends in the data series. The results showed that, on average, the rainfall exhibits an insignificant increasing tendency. It was also observed that there is, in general, an increasing trend in temperature (both maximum and minimum) in the study area. The analysis of the stream flows indicated that only one station (Bulbul Nr. Serbo) showed a positive slope at a 5% significance level. Two stations (Aweitu Nr. Babu and Gibe Nr. Seka) showed a slightly increasing trend, whereas the remaining 3 stations (Gibe Nr. Assendabo, Aweitu at Jimma, and Kitto Nr. Jimma) indicated an insignificant decreasing trend. The streamflow of the catchment generally shows a tiny decreasing tendency (0.007% per year) at its outlet. However, the results in general specified statistically insignificant trend changes of the hydrometrological data of the study catchment.
      PubDate: Thu, 25 Aug 2022 15:35:04 +000
       
  • Hydroclimatic Variability, Characterization, and Long Term Spacio-Temporal
           Trend Analysis of the Ghba River Subbasin, Ethiopia

    • Abstract: Understanding hydroclimatic variability and trend for the past four decades in the Upper Tekeze River basin is significant for future sustainable water resource management as it indicates regime shifts in hydrology. Despite its importance for improved and sustainable water allocation for water supply-demand and food security, varying patterns of streamflow and their association with climate change are not well understood in the basin. The main objective of this study was to characterize, quantify, and validate the variability and trends of hydroclimatic variables in the Upper Tekeze River basin at Ghba subbasin using graphical and statistical methods for homogeneous stations for the time period from 1953 to 2017, not uniform at all stations. The rainfall, temperature, and streamflow trends and their relationships were evaluated using the regression method, Mann–Kendall (MK) test, Spearman’s rho (SR) test, Sen’s slope, and correlation analysis. The analysis focused on rainfall, temperature, and streamflow collected from 11 climate and six hydrostations. For simplicity to discuss the interannual and temporal variability the stations were categorized into two clusters according to their record length, category 1 (1983–2017) and category 2 (1953–2017). About 73% and 27% of the rainfall stations exhibited normal to moderate annual rainfall variability. The MK and SR test showed that most of the significant trends in annual rainfall were no change except in one station decreasing and the test also showed no significant change in temperature except in three stations showed an increasing trend. Overall, streamflow trends and change point timings were found to be consistent among the stations and all have shown a decreasing trend. Changes in streamflow without significant change in rainfall suggest factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the subbasin. These research results offer critical signals on the characteristics, variability and trend of rainfall, temperature, and streamflow necessary to design improved and sustainable water allocation strategies.
      PubDate: Tue, 23 Aug 2022 10:20:03 +000
       
  • The Dew Particle Interception Abilities of Typical Plants in Northeast
           China Plant Leaves Capture Particles in Dew

    • Abstract: The dew condensation frequency is high, and the dew amount is heavy in urban ecosystems. During the condensation process, particulate matter acts as a condensation core, playing an important role in purifying the air. At night, dew mainly condenses on plant leaf surfaces, the plant leaves settle the particles in the dew, and some of the particles are resuspended into the atmosphere in the process of dew evaporation after sunrise. This paper monitored the condensation and evaporation processes of dew on four common plants in Changchun city from June to September 2020. By analyzing the mass and size of particles on different leaves after dew condensation and evaporation, the ability of different plants to retain particles in dew was analyzed. The results showed that there was no significant difference in the TSP capture ability during dew condensation between Buxus sinica (Rehd. et Wils.) Cheng subsp. sinica var. parvifolia M. Cheng, Syringa oblata Lindl., Hemiptelea davidii (Hance) Planch., and Pinus tabuliformis Carrière, with a TSP content of 0.21 ± 0.06 μg/cm2. Coarse particulate matter is the main type of deposit in the dew condensation stage. Particulate deposition varied according to species, leaf shape, and microstructure. The proportion of TSP remaining on leaves after dew evaporation from Pinus tabuliformis Carrière, Hemiptelea davidii (Hance) Planch., Buxus sinica (Rehd. et Wils.) Cheng subsp. sinica var. parvifolia M. Cheng, and Syringa oblata Lindl. tree was 89.7 ± 3.9%, 80.6 ± 3.6%, 75.9 ± 4.5%, and 71.4 ± 3.7%, respectively. The ability of the leaves to trap fine particles was significantly higher than that for coarse particles () after dew evaporation. The highest amount of particle captured by Syringa oblata Lindl. individual was 15.17 g/y during dew condensation, and the amount of remaining particles after dew evaporation was 10.83 g/y. This paper provides a theoretical basis for the selection of tree species for urban greening.
      PubDate: Thu, 18 Aug 2022 16:05:00 +000
       
  • Land-Atmosphere Energy Exchange Characteristics in Ali of Tibetan

    • Abstract: Based on the comprehensive data from the land-atmosphere interaction observation station in Ali of Tibetan in 2019, the characteristics of land-atmosphere energy exchange processes in Ali were analyzed. The results indicated that the timing of the mean intraday net radiation peak in Ali over the past 20 years has been delayed, and the month when the maximum monthly mean net radiation occurred has been delayed by about 2 months; the maximum daily mean, maximum monthly mean, minimum monthly mean, and annual mean sensible heat were 99.63 w/m2, 76.53 w/m2, 17.47 w/m2, and 46.74 w/m2, respectively, and the maximum daily mean, maximum monthly mean, minimum monthly mean, and annual mean latent heat flux were 73.27 w/m2, 36.13 w/m2, 0.67 w/m2, and 8.32 w/m2, respectively; and the monthly mean sensible heat was greater than the latent heat in all months.
      PubDate: Thu, 11 Aug 2022 06:35:01 +000
       
  • Deep Learning-Based English-Chinese Translation Research

    • Abstract: Neural machine translation (NMT) has been bringing exciting news in the field of machine translation since its emergence. However, because NMT only employs single neural networks to convert natural languages, it suffers from two drawbacks in terms of reducing translation time: NMT is more sensitive to sentence length than statistical machine translation and the end-to-end implementation process fails to make explicit use of linguistic knowledge to improve translation performance. The network model performance of various deep learning machine translation tasks was constructed and compared in English-Chinese bilingual direction, and the defects of each network were solved by using an attention mechanism. The problems of gradient disappearance and gradient explosion are easy to occur in the recurrent neural network in the long-distance sequence. The short and long-term memory networks cannot reflect the information weight problems in long-distance sequences. In this study, through the comparison of examples, it is concluded that the introduction of an attention mechanism can improve the attention of context information in the process of model generation of the target language sequence, thus translating restore degree and fluency higher. This study proposes a neural machine translation method based on the divide-and-conquer strategy. Based on the idea of divide-and-conquer, this method identifies and extracts the longest noun phrase in a sentence and retains special identifiers or core words to form a sentence frame with the rest of the sentence. This method of translating the longest noun phrase and sentence frame separately by the neural machine translation system, and then recombining the translation, alleviates the poor performance of neural machine translation in long sentences. Experimental results show that the BLEU score of translation obtained by the proposed method has improved by 0.89 compared with the baseline method.
      PubDate: Thu, 14 Jul 2022 06:50:01 +000
       
  • Nitrogen Inversion Model in a Wetland Environment Based on the Canopy
           Reflectance of Emergent Plants

    • Abstract: Reuse of reclaimed water in constructed wetlands is a promising way to conserve water resources and improve water quality, and it is playing a very important role in wetland restoration and reconstruction. This study utilized reflectance spectra of wetland vegetation to estimate nitrogen content in water in the Beijing Bai River constructed wetland, a typically constructed wetland that uses reclaimed water. Canopy reflectance spectra of two dominant plants in the wetland, including reed and cattail, were acquired using a spectrometer (350–2500 nm). Simultaneously, water samples were collected to measure water quality. To establish the appreciate relationship between total nitrogen content (TN) and reflectance spectra, both simple and multiple regression models, including simple ration spectral index (SR), normalized difference spectral index (ND), stepwise multiple linear regression (SMLR) model, and partial least squares regression (PLSR), were adopted in this study. The results showed that (1) compared with simple regression models (SR and ND), multiple regressions models (SMLR and PLSR) could provide a more accurate estimation of TN concentration in the wetland environment. Among these models, the PLSR model had the highest accuracy and was proven to be the most useful tool to reveal the relationship between the spectral reflectance of wetland plants and the total nitrogen consistency of wetland at the canopy scale. (2) The inversion effect of TN concentration in water is slightly better than that of wetland vegetation, and the reflection spectrum of the reed can predict TN concentration more accurately than that of cattail. The finding not only provides solid evidence for the potential application of remote sensing to detect water eutrophication but also enhances our understanding of the monitoring and management of water quality in urban wetlands using recycled water.
      PubDate: Thu, 14 Jul 2022 06:35:01 +000
       
  • The Influence of Rainfall and Evaporization Wetting-Drying Cycles on the
           Slope Stability

    • Abstract: The decay of soil strength and the change of soil infiltration characteristics caused by the dry and wet cycle effect generated by the rainfall-evaporation process are important factors that induce slope instability. How to consider the effect of soil strength decay and water-soil characteristic curve hysteresis effect on transient stability change of slope is the key to solve this problem. In this paper, transient stability analysis of slopes considering soil strength decay and water-soil characteristic curve hysteresis is carried out based on Geo-Studio. The results of the study showed that the change of transient safety factor of the slope caused by rainfall-evaporation dry and wet cycle process has an overall decreasing trend and the safety factor decreased by 43% compared to the initial state. The seepage characteristics of the rainfall-evaporation dry-wet cycle have certain regularity. The location of slope measurement points has a greater influence on the magnitude of the pore pressure change: foot of slope > middle of slope > top of slope. Also, there is a significant response hysteresis in the change of pore pressure with increasing depth at the same location. The rainfall intensity has a certain influence on the change of slope safety factor, but its influence is not obvious when the rainfall intensity exceeds a certain amount.
      PubDate: Sat, 09 Jul 2022 05:20:03 +000
       
  • Analysis of Observed Trends in Daily Temperature and Precipitation
           Extremes in Different Agroecologies of Gurage Zone, Southern Ethiopia

    • Abstract: Ethiopian climate-sensitive economy is particularly vulnerable to the effects of climate-related extreme events. Thus, examining extreme daily precipitation and temperature in the context of climate change is a critical factor in advocating climate change adaptation at the local scales. Spatial changes of climate indices for extreme precipitation and temperatures were conducted for the period 1986–2016 in three different agroecologies of the Gurage zone, Southern Ethiopia. The study used the Mann–Kendall (MK) test and Sen’s slope estimator to estimate the trend and magnitude of changes in precipitation and temperature. The analysis from the observation indicates that there had been a consistent warming trend and inconsistent changes in precipitation extremes in the study agroecologies. A statistically significant increase in the numbers of warm days and nights and a statistically significant reduction in the numbers of cold days and nights were observed in most of the agroecologies. The duration of extreme trend showed inconsistency; however, a drier condition is observed in lowland agroecology. Therefore, based on the findings of this study, appropriate climate adaptation efforts are needed at the local scale.
      PubDate: Thu, 07 Jul 2022 08:20:03 +000
       
  • A Review of the Impacts of Climate Change on Tourism in the Arid Areas: A
           Case Study of Xinjiang Uygur Autonomous Region in China

    • Abstract: Tourism is more sensitive and susceptible in global arid regions to climate change than other sectors, and climate change mainly affects the behavior of tourists, selection of tourist destinations, tourism resources, and tourism safety. China’s Xinjiang Uygur Autonomous Region (XUAR) is a representative area of the global arid region. To review its comprehensive impacts of climate change on tourism has indicative significance for the global arid region tourism industry to cope with climate change impacts. On the whole, the impacts of climate change on tourism in the XUAR will coexist with opportunities and challenges both at present and in the future. The XUAR is experiencing or will experience climatic process of warming and wetting. For the tourism climate comfort and extension of suitable travel period, the opportunities far outweigh the risks (high reliability). However, future climate change is expected to have great negative effects on cultural heritages, glacier and snow resources, and agricultural landscapes in arid areas of northwest China (high reliability). The above impacts are potential and long-term, and the measures should be taken as soon as possible to mitigate and adapt to climate change challenges to tourism.
      PubDate: Sat, 02 Jul 2022 05:35:01 +000
       
  • Meteorological Drought Monitoring Based on Satellite CHIRPS Product over
           Gamo Zone, Southern Ethiopia

    • Abstract: Drought is a frequent occurrence in semidesert areas of southern Ethiopia that significantly affect regional, social, economic, and environmental conditions. Lack of rainfall monitoring network, instrument measurement, and failure are major bottlenecks for agro-and hydroclimate research in developing countries. The objectives of this study were to evaluate the performance of CHIRPS rainfall product and to assess meteorological drought using SPI for the period 2000 to 2020 over Gamo Zone, southern Ethiopia. The performance of CHIRPS v2 was assessed and compared to station observations (2000–2020) in the study domain to derive SPI on a three-month timescale. The Pearson correlation coefficient (R), bias, probability of bias (PBias), mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and Nash simulation efficiency (NSE) values across the zone for CHIRPS v2 were found to be 0.88, 1.02, 2.56, 0.25, 22.41, 33.14, and 0.77, respectively. The results indicate that CHIRPS performed good ability to analyze the drought characteristics in the Gamo Zone. The spatial and temporal distribution method of meteorological drought has been evaluated using the Climate Data Tool (CDT). The Standardized Precipitation Index (SPI) was computed using the gamma distribution method. The magnitude of (SPI-3) of monthly and seasonal (MAM) meteorological drought in the zone from 2000 to 2020. The result shows that the known historic drought years (2014, 2015, 2010, 2009, and 2008) were indicated very well. Furthermore, sever and extreme droughts were observed in 2008 and 2009 with drought duration of 6.7 and 6.3, respectively, in most areas of the zone. Hence, this study revealed that CHIRPS can be a useful supplement for measuring rainfall data to estimate rainfall and drought monitoring in this region.
      PubDate: Tue, 28 Jun 2022 13:20:02 +000
       
  • Performance of MODIS Deep Blue Collection 6.1 Aerosol Optical Depth
           Products Over Indonesia: Spatiotemporal Variations and Aerosol Types

    • Abstract: This study aims to evaluate the performance of the long-term Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) Collection 6.1 (C6.1) in determining the spatiotemporal variation of aerosol optical depth (AOD) and aerosol types over Indonesia. For this purpose, monthly MODIS DB AOD datasets are directly compared with Aerosol Robotic Network (AERONET) Version 3 Level 2.0 (cloud-screened and quality-assured) monthly measurements at 8 sites throughout Indonesia. The results indicate that MODIS DB AOD retrievals and AERONET AOD measurements have a high correlation in Sumatra Island (i.e., Kototabang (r = 0.88) and Jambi (r = 0.9)) and Kalimantan Island (i.e., Palangkaraya (r = 0.89) and Pontianak (r = 0.92)). However, the correlations are low in Bandung, Palu, and Sorong. In general, MODIS DB AOD tends to overestimate AERONET AOD at all sites by 16 to 61% and can detect extreme fire events in Sumatra and Kalimantan Islands quite well. Aerosol types in Indonesia mostly consist of clean continental, followed by biomass burning/urban industrial and mixed aerosols. Palu and Sorong had the highest clean continental aerosol contribution (90%), while Bandung had the highest biomass burning/urban-industrial aerosol contribution to atmospheric composition (93.7%). For mixed aerosols, the highest contribution was found in Pontianak, with a proportion of 48.4%. Spatially, the annual mean AOD in the western part of Indonesia is higher than in the eastern part. Seasonally, the highest AOD is observed during the period of September–November, which is associated with the emergence of fire events.
      PubDate: Tue, 28 Jun 2022 07:05:01 +000
       
  • Evaluation of Hydropower Generation and Reservoir Operation under Climate
           Change from Kesem Reservoir, Ethiopia

    • Abstract: Climate changes significantly cause the precipitation deficiency and in turn reduce the inflow amount in reservoir affecting hydroelectric power generation. The primary objective of this study was to evaluate hydropower generation and reservoir operation under climate change from Kesem reservoir. Recent Representative Pathway (RCP) scenarios were used to evaluate the impact of climate change on power generation. Power transformation equation and variance scaling approach were amalgamated to adjust the bias correction of precipitation and temperature, respectively. Bias, root mean square error, and coefficient of variation were used to check the accuracy of projected rainfall. The base and future precipitation, temperature, and evaporation trend was analysed using the Mann–Kendall test. The flow calibration and validation were carried out by the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS), and hydropower generation was evaluated with reservoir simulation model (MODSIM 8.1) under climate scenarios. The performance of the model was found good with Nash–Sutcliffe coefficient (NSE) of 0.72 and coefficient of determination (R2) of 0.73 for calibration and NSE of 0.74 and R2 of 0.75 for validation. Projected future climate scenarios predicted increasing and decreasing trend of temperature and precipitation, respectively. For RCP4.5 climate scenario, the average energy generation is likely to decrease by 0.64% and 0.82% in both short-term (2021–2050) and long-term (2051–2080), respectively. In case of RCP8.5 climate scenario, the average energy generation will be decreased by 1.06% and 1.35% for short-term and long-term, respectively. Remarkable reduction of energy generation was revealed in RCP8.5 with relation to RCP4.5 scenario. This indicates that there will be high energy fluctuation and decreasing trend in the future energy generation. The research finding is crucial for decision-makers, power authorities, governmental and nongovernmental organizations, and watershed management agencies to take care for sustainability in the future hydropower generation in the Kesem reservoir.
      PubDate: Wed, 22 Jun 2022 15:20:01 +000
       
  • Estimation of Solar Insolation and Angstrom–Prescott Coefficients Using
           Sunshine Hours over Nepal

    • Abstract: The amount of solar insolation that reaches the Earth in one hour is sufficient to fulfill its annual energy budget. One of the challenges for harvesting this energy is due to a lack of relevant data. In the least developed countries like Nepal, the number of observation stations is insufficient. This data gap can be filled by employing credible empirical models to estimate solar insolation in regions where insolation measurements are not available. In this paper, Angstrom–Prescott model parameters are estimated for fifteen different locations of Nepal. Then, correlation is developed for the prediction of solar insolation using only sunshine hour data. The different statistical parameters such as root mean square error (RMSE = 1.958), mean bias error (MBE = −0.018), mean percentage error (MPE = 2.973), coefficient of residual mass (CRM = 0.001), and correlation coefficient (r = 0.909) were used to validate the developed coefficients. The resulting Angstrom–Prescott coefficients are a = 0.239 and b = 0.508. These coefficients can be utilized for the prediction of solar energy at different parts of the country in similar weather conditions.
      PubDate: Wed, 22 Jun 2022 07:35:01 +000
       
  • Progressive and Prospective Technology for Cloud Seeding Experiment by
           Unmanned Aerial Vehicle and Atmospheric Research Aircraft in Korea

    • Abstract: This study applies a novel cloud seeding method using an unmanned aerial vehicle (UAV) and a research aircraft in Korea. For this experiment, the UAV sprayed a cloud seeding material (calcium chloride), and the aircraft monitored the clouds in the southern part of the Korean Peninsula on April 25, 2019. Cloud observation equipment in the aircraft indicated an increase in the number concentration and average particle size of large cloud particles after the seeding. Weather radar reflectivity increased by approximately 10 dBZ above the experimental area due to the development of clouds and precipitation systems. Rain was observed after seeding, and 0.5 mm was recorded, including natural and mixed precipitation from the cloud seeding. In addition, it showed that the rapid increase in the number of raindrops and vertical reflectivity was approximately 10 dBZ. Therefore, these results showed the possibility of cloud seeding using UAVs and atmospheric research aircraft. The effects of cloud seeding are indicated through the increased number concentration and size of cloud particles, radar reflectivity, and ground-based precipitation detection.
      PubDate: Wed, 22 Jun 2022 06:05:01 +000
       
  • Research on the Optimization of Agricultural Industry Structure Based on
           Genetic Algorithm

    • Abstract: Due to the complexity and importance of optimizing and adjusting the crop planting structure in the Jianghuai hilly Tangba irrigation area between the upper reaches of the Huaihe River from Xinyang to the lower reaches of the Huaihe River in China, and based on experimental results from the Feidong Badou Irrigation Experiment Station, the farmland was modeled using rainfall and runoff data from the Tangba irrigation area. By examining the water balance of submerged irrigation, an optimization model of the agricultural industry structure was developed using genetic algorithms, and the model was solved using an accelerated genetic algorithm. Developing the research findings may provide scientific and technological support for adjusting the planting structure and formulation of irrigation systems in the Jianghuai Hills and Tangba irrigation area between the upper reaches of the Huaihe River and Xinyang, as well as significant practical guiding significance and application value.
      PubDate: Mon, 13 Jun 2022 01:50:01 +000
       
  • Solar GHI Ensemble Prediction Based on a Meteorological Model and Method
           Kalman Filter

    • Abstract: The intensity of light emanating from sun is determined by using a meteorological version and is altered with the numerical version, and the forecast accuracy is improved in advance by using Kalman Filter. As the accuracy of the version output related to its specific position is often questionable, group prediction constituting three members is suggested and agreed upon measurement. Also, this ensemble prediction provides an estimation of the solar global horizontal irradiance uncertainty (i.e., coverage rate of the prediction interval), which can be useful to provide flexible energy production forecasts. This article displays how the method Kalman filter could be used as an error correction way to alter the predicted irradiance value. The Kalman filter ameliorates the prediction of solar global horizontal irradiance as well as its interval. As the empirical coverage rate increases and closes to the nominal coverage rate, the interval size reduces.
      PubDate: Fri, 10 Jun 2022 04:35:00 +000
       
  • Statistical Learning-Based Spatial Downscaling Models for Precipitation
           Distribution

    • Abstract: The downscaling technique produces high spatial resolution precipitation distribution in order to analyze impacts of climate change in data-scarce regions or local scales. In this study, based on three statistical learning algorithms, such as support vector machine (SVM), random forest regression (RF), and gradient boosting regressor (GBR), we proposed an efficient downscaling approach to produce high spatial resolution precipitation. In order to demonstrate efficiency and accuracy of our models over traditional multilinear regression (MLR) downscaling models, we did a downscaling analysis for daily observed precipitation data from 34 monitoring sites in Bangladesh. Validation revealed that of GBR could reach 0.98, compared with RF (0.94), SVM (0.88), and multilinear regression (MLR) (0.69) models, so the GBR-based downscaling model had the best performance among all four downscaling models. We suggest that the GBR-based downscaling models should be used to replace traditional MLR downscaling models to produce a more accurate map of high-resolution precipitation for flood disaster management, drought forecasting, and long-term planning of land and water resources.
      PubDate: Tue, 07 Jun 2022 03:35:00 +000
       
  • Characteristics of Summer Precipitation in Chongqing Based on Hourly Rain
           Gauges Data

    • Abstract: Based on the hourly precipitation data of 34 meteorological stations in Chongqing in the summers (June to August) from 1996 to 2015, the spatial distribution and daily variation of precipitation amount (PA), precipitation intensity (PI), precipitation frequency (PF), and precipitation extremes in Chongqing are analyzed. The results show that, from the perspective of spatial distribution, the precipitation amount (PA) in Chongqing presents a distribution pattern of more around and less in the middle; the area with high precipitation intensity (PI) is mainly located in the northeast of Chongqing; the large value centers of precipitation frequency (PF) are located in the south and west of Chongqing and near Chengkou. On the spatial distribution of hourly precipitation, the precipitation in most areas of Chongqing is mainly concentrated at night [0200–0900 BT (1800–0100 UTC)], and the rain belt spreads from west to east with the passage of time. On the whole, interannual evolution characteristics of summer precipitation amount, precipitation intensity, and precipitation frequency in Chongqing are basically the same, showing a fluctuation characteristic without obvious trend, but there are some peaks and valleys. From the perspective of diurnal cycle, a larger peak of PA in Chongqing appears near 0300 BT (1900 UTC), another lower peak around 1200 BT (0400 UTC), a larger peak of PI around 0300 BT (1900 UTC), another smaller peak around 1500 BT (0700 UTC), and only one peak of PF around 0700 BT (2300 UTC). The extreme precipitation of different duration in summer in Chongqing is closely related to the topographic characteristics and weather system, the extreme centers of each diachronic precipitation are mainly located near Shapingba, Kaizhou, Youyang, and Shizhu, and the time evolution characteristics of the extreme precipitation are not obvious, but the trend of the extreme precipitation accumulated in 1 h, 3 h, 6 h, or 12 h is basically the same.
      PubDate: Thu, 02 Jun 2022 02:05:01 +000
       
  • The Effect of Humidity and Temperature on Indoor and Outdoor COVID-19
           Infections

    • Abstract: Environmental conditions and their association with COVID-19 have significantly attracted scientists’ attention. The current study links COVID-19 with climate indicators by comparing two configurations: indoor infections in a University of Duhok (UOD) building and outdoor infections within the boundaries of the Duhok Governorate (DG). The collected data included temperature and relative humidity (RH) and confirmed cases for indoor and outdoor configurations over 5 and 11 months, respectively. For the indoor infections, data were collected over the period of 5 weekdays, while for the outdoor infections, they were collected on the days when statistics were published. The prospective cross-section design was used for different statistical analyses. The overall indoor infections were very low, and the maximum values for RH and temperature were approximately
      PubDate: Wed, 01 Jun 2022 01:50:01 +000
       
  • Impact of Typhoons of Different Intensities on Short-Term Precipitation in
           the Middle and Lower Reaches of the Yangtze River in Summer

    • Abstract: According to China’s reanalyzed meteorological dataset (CN05.1), a 6-h track intensity typhoon meteorological dataset in the Western Pacific, three types of short-term precipitation are described to study the impact of typhoons on summer rainfall of different intensities in the middle and lower reaches of the Yangtze River: short-term extreme precipitation (95% quantile), short-term heavy precipitation (75% quantile), and normal precipitation (below the lower limit of the 75% quantile threshold). The results show that the amount of short-term extreme precipitation is 1.8 and 3.7 times that of normal precipitation and short-term heavy precipitation, respectively. Considerable interannual and interdecadal fluctuations in the proportion of short-term heavy precipitation and extreme precipitation during summer are affected by typhoons, with a wide range of changes occurring between 1980 and 2000. The areas with high amounts of short-term heavy precipitation and extreme precipitation are distributed mostly in the middle and southern parts of the middle and lower reaches of the Yangtze River, whereas areas with a high amount of normal precipitation are distributed mostly in the southeastern parts of the river. The spatial distribution of the three intensities of rainfall affected by typhoons is consistent, with a gradual decrease from southeast to northwest; in addition, the spatial distribution of the proportion of total summer rainfall has similar characteristics. The three intensities of precipitation are affected by the spatial distribution of the typhoon path frequency, and the distribution of the high-value areas is essentially the same as that of precipitation. This indicates that most of the typhoons that affect summer precipitation pass through the middle and lower reaches of the Yangtze River.
      PubDate: Tue, 31 May 2022 17:50:02 +000
       
  • Interaction Design of Educational App Based on Collaborative Filtering
           Recommendation

    • Abstract: With the advent of the 5G digital era, cell phones are becoming ubiquitous in all aspects of our lives, and the increasing demand for remote interaction makes the app interaction experience an indispensable part of our lives. Due to the operational characteristics of gesture interaction in the interface of a smart terminal application (app), this mode of human-computer interaction has become the mainstream mode of human-computer interaction. Educational app is the result of a combination between mobile Internet technology and education, which not only provides a more efficient and convenient method of learning for each subject but also expands the possibilities for teaching each subject through intelligent interaction. On this basis, this paper proposes an educational app design method based on collaborative filtering recommendations and investigates ways to improve the use of mobile apps to create an interactive teaching mode. Simultaneously, this paper combines user activity, item popularity, and time factors to comprehensively measure user visibility of items and incorporates them into the collaborative filtering recommendation algorithm in order to effectively mitigate the effects of data sparsity and user selection bias and improve recommendation results.
      PubDate: Sat, 28 May 2022 07:50:02 +000
       
 
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