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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Nature Climate Change     Full-text available via subscription   (Followers: 148)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 144)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Climatic Change     Open Access   (Followers: 69)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Advances in Climate Change Research     Open Access   (Followers: 57)
Journal of Climate     Hybrid Journal   (Followers: 56)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Change Economics     Hybrid Journal   (Followers: 48)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Atmospheric Science Letters     Open Access   (Followers: 40)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
American Journal of Climate Change     Open Access   (Followers: 38)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Atmosphere     Open Access   (Followers: 33)
Boundary-Layer Meteorology     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: 31)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 31)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 30)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Space Weather     Full-text available via subscription   (Followers: 28)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
Advances in Meteorology     Open Access   (Followers: 27)
Energy & Environment     Hybrid Journal   (Followers: 25)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
Climate Change Responses     Open Access   (Followers: 24)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 22)
International Journal of Environment and Climate Change     Open Access   (Followers: 22)
Tellus A     Open Access   (Followers: 21)
Current Climate Change Reports     Hybrid Journal   (Followers: 21)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 21)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
Global Meteorology     Open Access   (Followers: 20)
Journal of Economic Literature     Hybrid Journal   (Followers: 20)
Tellus B     Open Access   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weather and Climate Extremes     Open Access   (Followers: 18)
Weatherwise     Hybrid Journal   (Followers: 18)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 16)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 14)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 12)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Climate Risk Management     Open Access   (Followers: 10)
Climate Research     Hybrid Journal   (Followers: 9)
Climate     Open Access   (Followers: 8)
The Cryosphere (TC)     Open Access   (Followers: 8)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Climate and Energy     Full-text available via subscription   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 7)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Climate of the Past (CP)     Open Access   (Followers: 6)
Carbon Balance and Management     Open Access   (Followers: 6)
Climate Law     Hybrid Journal   (Followers: 6)
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)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Climate Services     Open Access   (Followers: 4)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Meteorological Applications     Open Access   (Followers: 4)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Atmospheric Environment : X     Open Access   (Followers: 3)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
Environmental and Climate Technologies     Open Access   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Atmósfera     Open Access   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Mediterranean Marine Science     Open Access   (Followers: 2)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Nīvār     Open Access   (Followers: 1)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Journal of Agricultural Meteorology     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  

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Advances in Meteorology
Journal Prestige (SJR): 0.48
Citation Impact (citeScore): 1
Number of Followers: 27  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-9309 - ISSN (Online) 1687-9317
Published by Hindawi Homepage  [339 journals]
  • 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
       
  • Harmonization and Verification of Three National European Icing Forecast
           Models Using Pilot Reports

    • Abstract: The Single European Sky Air Traffic Management Research (SESAR) program aims at modernizing and harmonizing the European airspace, which currently has a strongly fragmented character. Besides turbulence and convection, in-flight icing is part of SESAR and can be seen as one of the most important meteorological phenomena, which may lead to hazardous flight conditions for aircraft. In this study, several methods with varying complexities are analyzed for combining three individual in-flight icing forecasts based on numerical weather prediction models from Deutscher Wetterdienst, Météo-France, and Met Office. The optimal method will then be used to operate one single harmonized in-flight icing forecast over Europe. As verification data, pilot reports (PIREPs) are used, which provide information about hazardous weather and are currently the only direct regular measure of in-flight icing events available. In order to assess the individual icing forecasts and the resulting combinations, the probability of detection skill score is calculated based on multicategory contingency tables for the forecast icing intensities. The scores are merged into a single skill score to give an overview of the quality of the icing forecast and enable comparison of the different model combination approaches. The concluding results show that the most complex combination approach, which uses iteratively optimized weighting factors for each model, provides the best forecast quality according to the PIREPs. The combination of the three icing forecasts results in a harmonized icing forecast that exceeds the skill of each individual icing forecast, thus providing an improvement to in-flight icing forecasts over Europe.
      PubDate: Thu, 26 May 2022 07:50:01 +000
       
  • Detection Algorithm of Tennis Serve Mistakes Based on Feature Point
           Trajectory

    • Abstract: To address the issue of high recognition error in conventional action error detection methods, this article proposes a game of tennis serve error action detection algorithm based on feature point trajectory. To begin, a feature detection model for tennis serve images is established, followed by segmentation of the tennis serve images’ multiscale features. Second, the path of the tennis serving image is effectively corrected, thereby raising the bar for tennis training and competition. Additionally, a visual feature acquisition system for tennis serving action is being developed using remote video monitoring in order to correct the path of the serving image during play. The corner mark of the serving action error point is determined using this algorithm, and the optimal modeling of the tennis serving image’s path correction is realized using the developed edge segmentation algorithm. The results of simulations demonstrate that the aforementioned algorithm improves real-time performance and accuracy, and that it can accurately track players’ visual edge information feature points while they are serving, conduct real-time evaluation and guidance via an expert system, effectively correct the tennis serving image path, and enhance your capacity for service.
      PubDate: Tue, 24 May 2022 01:35:00 +000
       
  • Automatic Capture Processing Method of Basketball Shooting Trajectory
           Based on Background Elimination Technology

    • Abstract: The analysis and prediction of the shooting trajectory can be used to partially correct the shooting. The traditional automatic basketball shooting trajectory capture algorithm has a low capture accuracy and a long capture time, and thus is incapable of displaying the shooting trajectory in real time. To address this issue, this study proposes an automatic basketball shooting trajectory capture algorithm based on background elimination. The image of the basketball shooting trajectory is captured using imaging technology; the image is then preprocessed in four steps: binary erosion, binary expansion, closing operation, and opening operation to create a smooth image. After removing the background from the preprocessed image using the background difference method, the edge contour features are extracted, the candidate target area is set based on the extraction result, and a diagonal matrix reflecting the length and width of the trajectory target is introduced to calculate the probability of the color of the area in the shooting trajectory, thereby characterizing the trajectory. The target’s size changes in two directions to capture the basketball shooting trajectory automatically. The algorithm’s simulation results indicate that it has a higher accuracy and a shorter capture time.
      PubDate: Tue, 17 May 2022 11:35:02 +000
       
  • Climatic Factors Associated with Heavy Rainfall in Northern Vietnam in
           Boreal Spring

    • Abstract: Heavy rainfall occurs frequently in Northern Vietnam and causes severe floods and landslides. Heavy rainfall not only appears in rainy seasons (May–October) but also regularly occurs in spring (February–April). This study is devoted to identifying the climatic factors that influence the variation of rainfall, particularly heavy rainfall in Northern Vietnam in the dry season. Analysis based on the observed rainfall, PERSIANN satellite rainfall data, and ERA5 reanalysis reveals that spring should not be considered a dry season, but the first period of a rainy season in Northern Vietnam. Spring rainfall is caused by collaborative effects of cold surge, subtropical high, and the deepening of the low pressure over the Northeastern Tibetan Plateau and Bay of Bengal (BOB). Based on the composite analysis of heavy rainfall events in Northern Vietnam in the transitional season, two heavy rainfall patterns are recognized. The first is related to the southward movement of a meso-scale vortex and the cold surge, while the second one is induced by the interaction of cold surge and the deepening of an upper-level trough.
      PubDate: Sat, 14 May 2022 17:05:05 +000
       
  • An Integrated Framework for Mapping Nationwide Daily Temperature in China

    • Abstract: Air temperature (Ta) is an essential parameter for science research and engineering practice. While the traditional site-based approach is only able to obtain observations in limited and discrete locations, satellite remote sensing is promising to retrieve some environmental variables with spatially continuous coverage. Nowadays, land surface temperature (Ts) measurements can be obtained from some satellite sensors (e.g., MODIS), further enabling us to estimate Ta in view of the relationship between Ta and Ts. In this article, we proposed a two-phase integrated framework to estimate daily mean Ta nationwide. In the first phase, multivariate linear regression models were fitted between site-based observations of daily mean air temperature (Ta-mean) and MODIS land surface temperature products (including Terra day: TMOD-day, Terra night: TMOD-night, Aqua day: TMYD-day, and Aqua night: TMYD-night) conditional on some covariates of environmental factors. The fitted models were then used to predict Ta-mean from those covariates at unobserved locations. The predicted Ta-mean were looked on as stochastic variables, and their distributions were also obtained. In the second phase, Bayesian maximum entropy (BME) methods were used to produce spatially continuous maps of Ta-mean taking the meteorological station observations as hard data and the predicted Ta-mean in the first phase as soft data. It is shown that the proposed approach is promising to improve the interpolation accuracy significantly, comprehensively considering the prior knowledge and the context of space variability and correlation, which will enable it to compile spatially continuous air temperature products with higher accuracy.
      PubDate: Sat, 14 May 2022 03:35:01 +000
       
  • Comprehensive Evaluation and Error-Component Analysis of Four
           Satellite-Based Precipitation Estimates against Gauged Rainfall over
           Mainland China

    • Abstract: The Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) V06 product has been widely studied, but the errors and the source of the errors within IMERG over diverse climate regions still need to be quantified. To this end, the final run gauge-calibrated IMERG V06 (V06C) and uncalibrated IMERG V06 (V06UC) products are comprehensively evaluated here against 2088 precipitation gauges acquired between March 2014 and June 2018 over China. Moreover, V06C and V06UC rainfall estimates are compared against the Precipitation Estimation from Remotely Sensed Imagery using Artificial Neural Networks (PERSIANN)-Climate Data Record (CDR) and the Climate Prediction Center morphing technique (CMORPH) gauge-satellite blended (BLD) products. Continuous statistical indices and two error decomposition schemes are used to quantify their performance. Key results are as follows. (1) Except for V06UC’s relatively high underestimation over the Tibetan Plateau (TP) and high overestimation over Xinjiang (XJ), Northeastern China (DB), and Northern China (HB) and CDR’s severe overestimation over TP, all four satellite-based precipitation products can generally capture the spatial pattern of precipitation over China. Moreover, the satellite-based precipitation estimates agree better with gauge observations over humid regions than over semi-humid, semi-arid, and arid regions. (2) All the statistical indicators show that CDR has the worst performance, whereas BLD is the best precipitation product. As for the two IMERG products, V06C has improved V06UC’s precipitation estimate. Results show that the gauge calibration algorithm (GCA) used in IMERG has active effect in terms of r, POD, and CSI. (3) Within all subregions, all four satellite-based precipitation products demonstrate their worst performance over the arid XJ region which exhibits the highest FAR and lowest POD and CSI values among all regions. (4) In terms of intensity distribution, for summer over China, the four satellite-based precipitation products generally overestimate the frequency of moderate precipitation and light precipitation events (42 mm/day). (5) The relative bias ratio (RBR) analysis shows that the contribution of missed precipitation tends to be lower over wetter regions. In addition, for the same climate region, the contribution of missed precipitation is clearly lower in summer than in winter. In summer, false precipitation dominates the total error, whereas missed and false precipitation are the two leading error sources in winter. Future algorithm refinement efforts should focus on decreasing FAR in summer and winter and improving missed snow events during the winter.
      PubDate: Tue, 10 May 2022 09:35:01 +000
       
  • Evaluation Model of Eco-Environmental Economic Benefit Based on the Fuzzy
           Algorithm

    • Abstract: With the development of an ecological civilization gaining increasing attention in our country, an analysis of the environmental and economic impacts of all aspects of life has been developed gradually. However, because the study on the environmental and economic benefits of the tailwater diversion project is a weak link, the discussion on the environmental and economic benefits of the tailwater diversion project is novel. The variable fuzzy evaluation model is used to evaluate the comprehensive environmental and economic benefits of tailwater diversion engineering, in order to facilitate the exploration and application of tailwater diversion engineering. Simultaneously, by evaluating the method using the analytic hierarchy process and fuzzy optimum seeking method, linear comprehensive fuzzy optimization, average comprehensive fuzzy optimization, and variable fuzzy pattern recognition model of optimizing method, the results demonstrate that the method not only can be used to plan optimization but can also provide a good evaluation for each program, the result is reasonable and reliable, and applicable to the comprehensive benefits of water resource management.
      PubDate: Mon, 09 May 2022 11:35:03 +000
       
  • Statistics of the Performance of Gridded Precipitation Datasets in
           Indonesia

    • Abstract: Gridded precipitation datasets have been used as alternatives to rain gauge observations, but their applicability for a specific region should be thoroughly evaluated. This article aims at finding the most appropriate one for climatological and hydrological applications in Indonesia, by evaluating the statistics of the performance of eight different datasets (research products) having horizontal resolutions between 0.1 and 0.25 and with a time span of data availability from 2003 to 2015. The datasets are compared against the observed daily rainfall at 133 stations using 13 statistical metrics that can be classified into three groups with different characteristics of measurements, namely distribution, time sequence, and extreme value representations. By applying summation of rank (SR), it is found that MSWEP and TMPA 3B42 are the top two datasets that outperformed based on distribution and time sequence performance metric groups. The extreme performances for all datasets are still good in 75th percentiles; however, the performances decrease at more than 75th percentiles indicating still a poorly representation of daily extreme rainfall for all gridded datasets. Results of this study suggest that MSWEP (v2) is presently the best gridded precipitation datasets available for climatological and hydrological applications in Indonesia.
      PubDate: Mon, 09 May 2022 09:20:01 +000
       
  • Temporal-Spatial Characteristics and Future Changes of Temperature
           Extremes in Longtan Watershed Based on Multiple Indices

    • Abstract: Global warming and the intensification of extreme temperature events have been major issues around the world in recent decades. Understanding changes in temperature extremes is critical to assessing and responding to the risks associated with regional temperature change. This paper takes the Longtan watershed as the research object, and 11 extreme temperature indices were calculated based on the meteorological observation data from 1959 to 2017. The Mann-Kendall trend mutation test, Empirical Orthogonal Function, and other methods were used to explore the spatial and temporal distribution characteristics of temperature extremes. Meanwhile, the simulation effects of temperature were analyzed based on 11 CMIP5 climate models, and the extreme temperature change in 2021–2050 under the high emission scenario RCP8.5 and low emission scenario RCP4.5 was estimated. The main results are as follows: both the warm-related indices and the extreme minimum temperature show an increasing trend. The cold-related frequency indices all show a decreasing trend. The spatial distribution of most temperature extremes increases or decreases from southwest to northeast, and the fluctuation is obvious with the alternation of positive and negative positions of the time. In the next 30 years, compared with the reference period 1961–1990, under the RCP4.5, the multiyear average of the Extreme Tmax and the multiyear average of the Extreme Tmin increase by 2.1°C and 0.4°C, respectively, and by 2.0°C and 0.3°C under the RCP8.5. Overall, the frequency of extreme cold events decreases, and the frequency of extreme warm events increases. There is a warming trend in temperature extremes.
      PubDate: Tue, 03 May 2022 06:05:01 +000
       
  • Variation in the Positioning of the Asian Summer Monsoon Boundary in the
           Tibetan Plateau and Potential Drivers

    • Abstract: Studying the variation in the boundary position of the Asian summer monsoon in the Tibetan Plateau (TP) region and its potential drivers is important for understanding the climate in this region. Three sets of mean monthly precipitation data from 1980 to 2019 were sourced from the Global Precipitation Climatology Centre, the Climate Research Unit, and China Meteorological Information Service Centre. Several indicators that represent the Asian summer monsoon boundary (ASMB) were selected to compare their applicability to the TP region and elucidate the changes in the location of the ASMB in the TP over the last four decades. The results showed that the ASMB in the TP region extends in a southwest-northeast direction, with a clear north-south variation. It reaches as far north as the Kunlun Mountains and as far south as the Himalayas. The largest amplitude in spatial fluctuation occurs in the middle of the TP, and the smallest amplitude occurs at both ends of the region. A “small-large-small” fluctuation pattern was observed from west to east. The water vapor mainly originates from the South Asian region. The South Asian summer monsoon can move the ASMB position northward, whereas the westerly wind moves the ASMB position southward. Variation in the ASMB in the TP region is closely associated with the South Asian monsoon and westerly wind.
      PubDate: Sat, 30 Apr 2022 05:50:03 +000
       
  • Research on Tourism Resource Evaluation Based on Artificial Intelligence
           Neural Network Model

    • Abstract: The rational evaluation of tourism resources and the discovery of valuable potential tourism resources are important foundations for promoting the development of tourism industry. This paper systematically reviews the development history of China’s ethnic tourism resource evaluation, analyzes the three different stages of tourism resource evaluation changes and their basic characteristics, and conducts research on tourism resource evaluation based on artificial intelligence neural network model to avoid the influence of subjective factors on the evaluation results to the greatest extent. This paper uses the literature comparison method, theoretical analysis method, and expert consultation method to construct an evaluation index system containing 5 primary indicators and 12 secondary indicators on the basis of which an evaluation model is designed focusing on the error values in the evaluation model, and the evaluation model is applied to the evaluation of tourism resources in several major cities, and its evaluation results and error ranges meet the requirements.
      PubDate: Thu, 28 Apr 2022 15:20:01 +000
       
  • Research on the Design of Public Space in Urban Renewal Based on
           Multicriteria Cluster Decision-Making

    • Abstract: Urban design is a critical technical tool for shaping and intervening in urban space, but it is also developing into a critical governance tool for guiding the orderly development of urban renewal, thereby contributing significantly to its effectiveness. This paper examines the design of public space in urban renewal through the lens of multicriteria group decision-making, introduces urban design governance theory, develops a theoretical framework for instrumentalizing urban design governance to respond to various levels of urban renewal, and investigates strategies for assisting urban renewal through the innovation of governance subjects and semiformal governance tools, in addition to the formal path of combining urban design and planning. Simultaneously, a multicriteria decision-making algorithm is proposed that combines theoretical concepts from the fields of computational intelligence and multicriteria decision-making, adopts a normalization fundamental model to standardize the attribution function, selects valid data information function values to combine into an aggregation function, and then establishes a multicriteria approach to deal with heterogeneous information based on the aggregation function. The experimental results demonstrate that the proposed algorithm is capable of coping with and representing the imprecision and uncertainty inherent in the input data.
      PubDate: Wed, 27 Apr 2022 14:50:01 +000
       
  • The Prediction Algorithm and Characteristics Analysis of Kuroshio Sea
           Surface Temperature Anomalies

    • Abstract: Based on 130 climate signal indexes provided by National Climate Center of China, this paper established a decision tree diagnostic prediction model for Spring Kuroshio Sea Surface Temperature (SST) from 1961 to 2015 (65 years) by using Chi-Squared Automatic Interaction Detector (CHAID) algorithm in data mining and obtained five rule sets to determine whether Spring Kuroshio SST is high or not. Considering the data of the 44 years from 1961 to 2004 as the training set of the model and the other years as the test set, the training accuracy of the model can reach to 95.45% and the test accuracy can reach to 81.82%. Three types of Spring Kuroshio SST are different in intensity and distribution. The results show that the prediction model of Spring Kuroshio SST based on CHAID algorithm has a high prediction accuracy, with the reasonable and effective model and the well-thought-out decision rules. Moreover, based on the results of decision classification, the SST anomalies correspond to different distribution characteristics of summer daily precipitation anomalies in eastern China, which can provide a new idea and method for climate prediction of regional summer precipitation.
      PubDate: Wed, 27 Apr 2022 08:35:02 +000
       
  • Reduced Air Pollution during the Prevailing of COVID-19 Pandemic: Five
           Years Observation and Path Analysis in the Fenwei Plain, Northwest China

    • Abstract: Heavy pollution in North China has attracted extensive attention in recent decades, and numerous studies have been conducted in developed regions, while studies on the heavily polluted Fenwei Plain in Northwest China are still scarce. In this study, we analyzed the continuous air pollution records of Weinan city on the Fenwei Plain from 2016 to 2020 to provide specific prevention and control strategies for the region. From 2016 to 2020, pollutant concentrations showed an overall decreasing trend, with a slight increase in O3 concentration. The study found that during the COVID-19 lockdown period, O3 was also significantly affected by the lockdown policy. During the prevailing COVID-19 pandemic in 2020, anthropogenic emissions were reduced due to restraints on commercial and social activities. NO2 responds sensitively during COVID-19, and PM2.5 has a delayed response. We applied pathway analysis to investigate the contribution of different pollutants and meteorology to PM2.5. The results show that CO and NO2 have the largest positive comprehensive effect, while wind speed and temperature have the largest negative comprehensive effect. Spearman’s correlation analysis shows that NO2 contributes significantly to O3 production in different AQI ranges. We advocate that the NOx should be given more attention and become the new focus of air control.
      PubDate: Wed, 27 Apr 2022 06:50:00 +000
       
  • Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in
           Sri Lanka

    • Abstract: The availability of accurate spatiotemporal rainfall data is of utmost importance for reliable predictions from hydroclimatological studies. Challenges and limitations faced due to the absence of dense rain gauge (RG) networks are seen especially in the developing countries. Therefore, alternative rainfall measurements such as satellite rainfall products (SRPs) are used when RG networks are scarce or completely do not exist. Noteworthy, rainfall data retrieved from satellites also possess several uncertainties. Hence, these SRPs should essentially be validated beforehand. The Mahaweli River Basin (MRB), the largest river basin in Sri Lanka, is the heart of the country’s water resources contributing to a significant share of the hydropower production and agricultural sector. Given the importance of the MRB, this study explored the suitability of SRPs as an alternative for RG data for the basin. Daily rainfall data of six types of SRPs were extracted at 14 locations within the MRB. Thereafter, statistical analysis was carried out using continuous and categorical evaluation indices to evaluate the accuracy of SRPs. Nonparametric tests, including the Mann-Kendall and Sen’s slope estimator tests, were used to detect the possibility of trends and the magnitude, respectively. Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) outperformed among all SRPs, while Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products showed dire performances. However, IMERG also demonstrated underestimations when compared to RG data. Trend analysis results showcased that the IMERG product agreed more with RG data on monthly and annual time scales while Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis–3B42 (TRMM-3B42) agreed more on the seasonal scale. Overall, IMERG turned out to be the best alternative among the SRPs analyzed for MRB. However, it was clear that these products possess significant errors which cannot be ignored when using them in hydrological applications. The results of the study will be valuable for many parties including river basin authorities, agriculturists, meteorologists, hydrologists, and many other stakeholders.
      PubDate: Mon, 25 Apr 2022 09:35:01 +000
       
  • Estimation of Potential Evapotranspiration across Sri Lanka Using a
           Distributed Dual-Source Evapotranspiration Model under Data Scarcity

    • Abstract: Evapotranspiration estimations are not common in developing countries though most of them have water scarcities for agricultural purposes. Therefore, it is essential to estimate the rates of evapotranspiration based on the available climatic parameters. Proper estimations of evapotranspiration are unavailable to Sri Lanka, even though the country has a significant agricultural contribution to its economy. Therefore, the Shuttleworth–Wallace (S-W) model, a process-based two-source potential evapotranspiration (PET) model, is implemented to simulate the spatiotemporal distribution of PET, evaporation from soil (ETs), and transpiration from vegetation canopy (ETc) across the total landmass of Sri Lanka. The country was divided into a grid with cells. The meteorological data, including rainfall, temperature, relative humidity, wind speed, net solar radiation, and pan evaporation, for 14 meteorological stations were used in this analysis. They were interpolated using Inverse Distance Weighting (IDW), Universal kriging, and Thiessen polygon methods as appropriate so that the generated thematic layers were fairly closer to reality. Normalized Difference Vegetation Index (NDVI) and soil moisture data were retrieved from publicly available online domains, while the threshold values of vegetation parameters were taken from the literature. Notwithstanding many approximations and uncertainties associated with the input data, the implemented model displayed an adequate ability to capture the spatiotemporal distribution of PET and its components. A comparison between predicted PET and recorded pan evaporations resulted in a root mean square error (RMSE) of 0.75 mm/day. The model showed high sensitivity to Leaf Area Index (LAI). The model revealed that both spatial and temporal distribution of PET is highly correlated with the incoming solar radiation fluxes and affected by the rainfall seasons and cultivation patterns. The model predicted PET values accounted for 80–90% and 40–60% loss of annual mean rainfall, respectively, in the drier and wetter parts of the country. The model predicted a 0.65 ratio of annual transpiration to annual evapotranspiration.
      PubDate: Sat, 23 Apr 2022 08:50:03 +000
       
  • Variability of the Minor Season Rainfall over Southern Ghana
           (1981–2018)

    • Abstract: The monitoring of rainfall variability over recent decades has become a necessity due to its devastating effects such as floods and droughts, which render humans vulnerable across different parts of the West African region. The current study seeks to provide a good understanding of variability within the minor rainfall season over southern Ghana by employing statistical tools to quantify variability in rainfall. Daily rainfall data from 1981 to 2018 for seventeen (17) synoptic weather stations across southern Ghana are used for this analysis. We perform trend and descriptive statistics of rainfall amount and extreme indices intending to identify the areas with the greatest variability in rainfall. Further, for five recent years (2014–2018), we do an interpolation of the ground station rainfall data and compute anomalies. We find increasing trends of rainfall in the minor rainy season for 16 out of the 17 stations, with rainfall increasing between 0.10 mm and 4.30 mm each season. For extreme rainfall indices, the 17 stations show nonsignificant trends of very wet and extremely wet days. We also find that the middle parts of Ghana have the highest rainfall amounts (262.7 mm/season–400.2 mm/season), while the East Coast has the lowest (125.2 mm/season–181.8 mm/season). Over the whole of southern Ghana, we find high variability in rainfall amount with the coefficient of variations (CV) between 25.3% and 70.8% and moderate to high variability in rainfall frequency (CV = 14.0%–48.8%). The results of rainfall anomalies show that the middle parts had an above-normal rainfall amount. In the same period, the transition areas experienced below-normal rainfall. Our finding of high variability in the minor rainfall season has implications for agricultural productivity in Ghana and countries in the West African region, which rely heavily on rain-fed agriculture. Hence, this study recommends more research to understand the causes of variability in the West African monsoon and how this will change in the region.
      PubDate: Fri, 22 Apr 2022 03:05:02 +000
       
  • Hydrological Drought Analysis using Streamflow Drought Index (SDI) in
           Ethiopia

    • Abstract: Drought is a natural disaster that has impacts on society, the environment, and the ecosystem. Ethiopia faced many horrible severe drought events in the last few decades. Even though there are some drought-related studies in the country, most of the investigations were focused on meteorological drought analysis. This study was focused on hydrological drought analysis in Ethiopia using the streamflow drought index (SDI). The main objective was to identify drought-prone areas and severe drought events years. Streamflow data were collected from 34 stations to analyze SDI in seasonal (3-month) and annual (12-month) timescales. The analysis implies that seasonal time scale (3-month) hydrological drought has a high frequency of occurrence but short duration, whereas annual (12-month) analysis has a low frequency with a large magnitude. The overall result shows that 1984/85, 1986/87, 2002/03, and 2010/11 were the most severe and extreme drought years in all river basins. The 1980s were found severe and extreme drought years in which most hydrological drought events occurred in the country. The spatial analysis shows that Tekeze, Abbay, and Baro river basins have similar characters; Awash and Rift Valley River basins show relatively the same character, and Genale Dawa and Wabishebele river basins have a similar character. But Omo Gibe River basin has a unique character in which the severe drought occurred in a different year of other river basins.
      PubDate: Fri, 22 Apr 2022 03:05:01 +000
       
  • Climate Change Adaptation Strategies for Hydropower Development in Sondu
           Miriu Basin

    • Abstract: Hydropower is sustainable and environmentally friendly source of energy worldwide. Driven by streamflow, it is vulnerable to climate change and land use change. The hydropower production from the two existing run-of-river hydropower projects on the Sondu Miriu River is vulnerable to rainfall variability and requires strategies for building resilience for the local communities. The objective of this study was to identify appropriate and sustainable strategies for integrating climate change adaptation into hydropower development within the Sondu Miriu River Basin. The methodology involved review of existing climate change adaptation strategies to identify appropriate strategies for integrating climate change adaptation in hydropower developments within the Sondu Miriu River Basin. The results indicate that no clear climate change adaptation strategies are being implemented within the basin. A framework is needed to implement appropriate climate change adaptation strategies within the basin. Climate Change act of 2016 created linkage with other existing policies for effective support of integration of climate change adaptation into hydropower development in Sondu Miriu River Basin. Strengthening community resilience to climate change impacts is one of the benefits to be derived from the hydropower projects by supporting appropriate adaptation strategies.
      PubDate: Thu, 21 Apr 2022 06:50:02 +000
       
  • A Personalized Recommendation Method for Short Drama Videos Based on
           External Index Features

    • Abstract: Dramatic short videos have quickly gained a huge number of user views in the current short video boom. The information presentation dimension of short videos is higher, and it is easier to be accepted and spread by people. At present, there are a large number of drama short video messages on the Internet. These short video messages have brought serious information overload to users and also brought great challenges to short video operators and video editors. Therefore, how to process short videos quickly has become a research hotspot. The traditional episode recommendation process often adopts collaborative filtering recommendation or content-based recommendation to users, but these methods have certain limitations. Short videos have fast dissemination speed, strong timeliness, and fast hot search speed. These have become the characteristics of short video dissemination. Traditional recommendation methods cannot recommend short videos with high attention and high popularity. To this end, this paper adds external index features to extract short video features and proposes a short video recommendation method based on index features. Using external features to classify and recommend TV series videos, this method can quickly and accurately make recommendations to target customers. Through the experimental analysis, it can be seen that the method in this paper has a good effect.
      PubDate: Mon, 18 Apr 2022 05:35:02 +000
       
 
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