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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: 45)
Advances in Climate Change Research     Open Access   (Followers: 49)
Advances in Meteorology     Open Access   (Followers: 27)
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: 36)
Atmósfera     Open Access   (Followers: 2)
Atmosphere     Open Access   (Followers: 33)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Science Letters     Open Access   (Followers: 40)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Carbon Balance and Management     Open Access   (Followers: 6)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate     Open Access   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 6)
Climate Change Economics     Hybrid Journal   (Followers: 44)
Climate Change Responses     Open Access   (Followers: 23)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Climate Law     Hybrid Journal   (Followers: 6)
Climate of the Past (CP)     Open Access   (Followers: 6)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Research     Hybrid Journal   (Followers: 9)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Climate Risk Management     Open Access   (Followers: 10)
Climate Services     Open Access   (Followers: 4)
Climatic Change     Open Access   (Followers: 69)
Current Climate Change Reports     Hybrid Journal   (Followers: 17)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 13)
Energy & Environment     Hybrid Journal   (Followers: 24)
Environmental and Climate Technologies     Open Access   (Followers: 3)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 21)
Frontiers in Climate     Open Access   (Followers: 4)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 20)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 29)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
International Journal of Environment and Climate Change     Open Access   (Followers: 20)
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: 133)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Journal of Climate     Hybrid Journal   (Followers: 56)
Journal of Climate Change and Health     Open Access   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 21)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
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: 29)
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: 13)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Nature Climate Change     Full-text available via subscription   (Followers: 145)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Nīvār     Open Access   (Followers: 1)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
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: 32)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Urban Climate     Hybrid Journal   (Followers: 5)
Weather     Hybrid Journal   (Followers: 20)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Weather and Climate Extremes     Open Access   (Followers: 18)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
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: 27  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-9309 - ISSN (Online) 1687-9317
Published by Hindawi Homepage  [339 journals]
  • 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

    • 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

    • 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

    • 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

    • 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
  • Analysis of the Most Common Aviation Weather Hazard and Its Key Mechanisms
           over the Yangon Flight Information Region

    • Abstract: The aviation industry has a global economic impact of $2.7 trillion (including direct, indirect, induced, and tourism catalytic effects) and contributes 3.6 percent of global GDP. Weather is one of the most essential elements impacting how an aircraft runs and how safely it can fly. The correlation coefficient is the most significant index explaining the relationship between variables and can result in teleconnection patterns of climate indices. El Nino-Southern Oscillation (ENSO) and India Ocean Dipole (IOD) were used in this study based on the ERA5 reanalysis dataset for 30 years (1991–2020). Myanmar’s Yangon International Airport has recorded more than 119874 times of observation data from 2009 to 2019. The mean percentage of occurrences of weather elements is calculated for each month and each season. Analysis of flight delay and accident data was obtained statistically from the Aviation Safety Network (ASN). According to the monthly delay index, July, August, and March are the maximum delay index months, and the correlation value between aircraft movement and delays is maximum in July and August and minimum in January and February. After examining numerous characteristics of Yangon International Airport, we identified which elements had a big impact on operations through vital interviews with operators, the accident case study section, and climatology analysis. As a result, we identified two meteorological occurrences: thunderstorm rain (TSRA) and fog (FG) are of high frequency and TSRA poses a larger risk than FG for aviation operation. The maximum frequency (%) of thunderstorm occurrences was 22% in July and the minimum was 1% in January. Annual frequency analysis revealed that TSRA days are becoming more common year after year as a result of global climate change. According to a spatial gridded analysis by ERA5 reanalysis data (1991–2020), the annual convective available potential energy (CAPE) values over local airport regions, the Bay of Bengal (BOB), the western equatorial Pacific, and the South China Sea show a positive correlation with convective rainfall. In contrast, negative convective inhibition (CIN) anomalies have been observed over the same areas as above, except for the western part of BOB along the Indian Coast. The primary innovation is that we look at the effects of thunderstorms on airport operations before determining their link with ENSO and the IOD individually and then combining them during their full phases. This raises a new question and a new possibility for viewing climatology from a new perspective.
      PubDate: Fri, 15 Apr 2022 11:50:01 +000
  • Separating the Impact of Climate Changes and Human Activities on
           Vegetation Growth Based on the NDVI in China

    • Abstract: Vegetation growth is affected by both climate changes and human activities. In this study, we investigated the vegetation growth response to climate change (precipitation and temperature) and human activities in nine subregions and for nine vegetation types in China from 1982 to 2015. The normalized difference vegetation index (NDVI) and the RESTREND method based on a multiple linear regression model were employed to this end. An overall increasing trend in the NDVI was observed in recent decades, and the fastest increases were identified in southern China (TrendNDVI = +0.0190) and evergreen broad-leaved forests (TrendNDVI = +0.0152). For >66% of China, vegetation is more sensitive to temperature and less sensitive to precipitation based on the regression coefficients. The water demand for vegetative growth increased significantly from 1999 to 2015 with global warming, especially in parts of the temperate zone. We defined a relative change in the residual trend to quantify the impact of human activities on vegetation. in two periods (P1, 1982–1998 and P2, 1999–2015) markedly increased, indicating that human activities play a key role in the reversal of land degradation.
      PubDate: Tue, 12 Apr 2022 09:20:00 +000
  • A Novel Approach for Monitoring the Ecoenvironment of Alpine Wetlands
           using Big Geospatial Data and Cloud Computing

    • Abstract: Alpine wetlands in western Sichuan plateau (WSCP) are located on the eastern edge of the Qinghai-Tibet Plateau (QTP), where the ecological environment is very sensitive to global climate change. Being naturally driven coupled with unreasonable human development activities, alpine wetlands have experienced serious ecological and environmental issues such as drought, inversion, and desertification. However, due to the limitations of data sources and calculation models, it is impossible for us to deeply understand the change mechanism and spatial difference of the ecological environment of the alpine wetland (EEAW) in previous studies. In view of this, an innovative approach for monitoring the EEAW change has been proposed in this paper. We employ the approach to perform the EEAW change trend analysis, and some meaningful characteristics were founded. Specifically, it includes the fol1owing aspects. The air temperature increase is relatively significant, while the precipitation change has obvious spatial differentiation, and even some region’s precipitation experienced a decrease especially in plot1. In Haizishan, Lugu Lake, and Bari Lake, we explored an interesting phenomenon that the precipitation increases first and then decrease, and the turning point occurred around 1999. Increases in air temperature and evaporation have aggravated the drought in high-latitude areas. The drought situation has been alleviated in high-altitude areas due to the acceleration of snow melt water. Wetland vegetation and biomass presented an overall increasing trend, but the degradation also occurs in some area, including Zoige and Lugu Lake area. The human activity disturbances of wetland degradation mainly include the settlements expansion, agricultural development, and the ecotourism prosperity. Among them, targeted poverty alleviation projects have accelerated the urbanization in WSCP, and the development of agriculture and tourism has increased the interference of wetlands. Additionally, we have used Landsat images and national wetland survey data (1999, 2013, and 2020 year) from the past two decades to verify the EEAW trend and confirm the reliability of the analysis results using this approach.
      PubDate: Tue, 12 Apr 2022 08:05:01 +000
  • Study on Meteorological Disaster Monitoring of Field Fruit Industry by
           Remote Sensing Data

    • Abstract: Meteorological disasters have brought a great negative impact on people’s lives. With the rapid development of modern science and technology, the detection technology of meteorological disasters has been continuously improved. At present, satellite remote sensing detection technology has made gratifying achievements, and it has a good application in meteorological disaster prediction. In this paper, the application of satellite remote sensing technology in the process of meteorological disaster monitoring is discussed in depth. In traditional work, the accuracy and timeliness of meteorological disaster monitoring is the key and difficult point of meteorological disaster prevention. Using satellite telemetry to monitor meteorological disasters can effectively improve the accuracy and timeliness of meteorological disaster monitoring, provide reasonable solutions and decision-making basis for meteorological disaster prevention, and achieve the purpose of disaster prevention and mitigation. This paper introduces the basic principle, technical system, and important role of satellite remote sensing technology, expounds on the application of satellite remote sensing technology in the monitoring of agricultural meteorological disasters such as water, drought, freezing, and hail, and provides a scientific reference for farmers, agricultural sustainability, and agricultural decision-making. The continuous development of our country’s modern social economy has put forward higher requirements for agricultural production. Traditional monitoring technology can no longer meet the needs of agricultural meteorological disaster monitoring. The scientific application of remote sensing monitoring technology has important value, which can effectively improve the detection level and make it have higher accuracy and real-time performance, thereby promoting modern agricultural production in China. Based on the analysis of the application value of remote sensing monitoring technology, this paper comprehensively discusses the specific conditions of different disasters monitored by remote sensing monitoring technology in agricultural production.
      PubDate: Tue, 12 Apr 2022 08:05:01 +000
  • Parameter Sensitivity Analysis and Optimization of the Single-Layer Urban
           Canopy Model in the Megacity of Shanghai

    • Abstract: In order to meet the demand of more refined urban weather forecast, it is of great practical significance to improve and optimize the single-layer urban canopy model (SLUCM) suitable for the megacity of Shanghai. In this paper, based on the offline SLUCM model driven by a whole-year surface flux observation data in the Shanghai central business district, a series of parameter sensitivity tests are carried out by using the one at a time (OAT) method, the relative importance and a set of optimized parameters of the SLUCM suitable for high-density urban area are established, and the improvement of simulation is evaluated. The results show that SLUCM well reproduces the seasonal mean diurnal patterns of the net all-wave radiation flux () and sensible heat flux (QH) but underestimates their magnitudes. Both and QH are linearly sensitive to the albedo, and most sensitive to the roof albedo, the second to the wall albedo, but relatively insensitive to the road albedo. The sensitivity of and QH to emissivity is not as strong as that of albedo, and the variation trend is also linear. Similar to albedo, and QH are most sensitive to roof emissivity. The effect of thermal parameters (heat capacity and conductivity) on fluxes is logarithmic. The sensitivity of surface fluxes to geometric parameters has no specific variation pattern. After parameter optimization, RMSE of decreases by about 3.4–18.7 Wm−2 in four seasons. RMSE of the longwave radiation (L↑) decreases by about 1.2–7.87 Wm−2. RMSE of QH decreases by about 2–5 Wm−2. This study provides guidance for future development of the urban canopy model parameterizations and urban climate risk response.
      PubDate: Mon, 11 Apr 2022 10:50:02 +000
  • Impact of Hydroclimate Change on the Management for the Multipurpose
           Reservoir: A Case Study in Meishan (China)

    • Abstract: China holds the largest amount of reservoirs in the world, while more than 80% of them were constructed 50–70 years ago and are approaching a critical stage of their designed lifetime. Before deciding the future of a reservoir, it is essential to find out whether it could still satisfy its original purpose in the context of hydroclimate change under global warming. Here, we present a case study of the Meishan reservoir in east-central China, which was primarily built for irrigation and flood control in the 1950s. We evaluate the impacts of rainfall change on the hedging and releasing rules over the historical period (1969–2008) by instrumental data and future period (2061–2100) based on simulations in a regional rivalry-mitigated scenario from the Coupled Model Intercomparison Project Phase 6. The main conclusions are as follows: (1) the annual total rainfall has a remarkable increasing trend from 2015 to 2100 and the annual precipitation variability exceeds the envelope range during the past 50-year period. The increased precipitation amount mainly occurs in spring (March to May). (2) The optimal regulation cycle is from September to August and from July to June for both historical and future periods. The limiting level during the nonflooded season is lower than the operating water level for more than five months in the historical period, which limits the ability of reservoir regulation and utilization of water resources. However, the water supply is no longer affected by flood control in 2061–2100 because of the redistribution of annual precipitation. (3) The projected irrigation and residential water demands of the Meishan reservoir are stable; thus, the improvement of the total economic benefit will mainly depend on power generation. This case provides a practical guide for many reservoirs serving water supply for small cities in eastern China, where the size of the population and cultivated land area is stagnant and the climate is getting wetter.
      PubDate: Wed, 30 Mar 2022 13:50:01 +000
  • Overview of the Application of Orographic Data in Numerical Weather
           Prediction in Complex Orographic Areas

    • Abstract: Complex orography is still a big challenge for all numerical weather prediction (NWP) models. Orography is an important factor that affects the NWP results. The orography in NWP mainly affects the main accuracy of the results through two aspects: orographic representation in models dynamics and orography-related parameterization schemes in the physical processes. To ensure the accuracy of NWP results, it is necessary to have a comprehensive understanding of the application of orographic data in NWP. This paper summarized the influence of orography on weather, the influence of orographic representation on prediction accuracy, and the parametrization of orography-related drag in NWP models. Finally, this paper elaborates the problems of the application of orographic data in NWP and looks forward to future directions in this field, hoping to improve the performance of NWP in complex orographic areas and provide a reference for better application in NWP.
      PubDate: Wed, 30 Mar 2022 09:50:01 +000
  • Sources of Forecast Errors for Rainstorms in the South China Monsoon

    • Abstract: The possible sources of forecast errors associated with rainstorms in the South China monsoon region were investigated based on Weather Research and Forecasting (WRF) model forecasts for 19 rainstorm cases that occurred in the past 13 years. Two datasets were separately selected as the initial fields of WRF with the same physical parameterization schemes. By investigating the improvement rate of the forecast when using one set of data rather than the other, the important degree of the initial conditions with respect to the forecasts for each case has been obtained. For those initial errors are the important sources of forecast errors, we further explored the source of the initial errors by comparing the two initial conditions. It was found that, interestingly, the significant differences between two initial conditions are all located upstream the rainfall area, with a distance of 5° of longitude away and an area of about 4° × 4°. Based on this, we developed a new method (which we refer to as the “guide flow method”) to identify the sensitive area for rainstorm forecasts in the South China monsoon region and then examined the efficiency of the sensitive areas. It was found that reducing the initial errors in the sensitive areas leads to better forecast results than doing the same in other areas. Thus, the sensitive areas are the source areas of forecast errors for rainstorms in the South China monsoon region.
      PubDate: Sat, 26 Mar 2022 07:35:02 +000
  • Air Pollutants Sources in Winter in Chang-Zhu-Tan Region of China

    • Abstract: In order to analyze the primary sources of air pollutants in Chang-Zhu-Tan region, this article selected the environmental monitoring data and meteorological data in the winter of 2019 to calculate the backward airflow trajectories with the Chang-Zhu-Tan region as the starting point by using the backward trajectory model. Combined with the ground concentration monitoring data, cluster analysis, potential source contribution factor (PSCF) analysis, and concentration weighted trajectory (CWT) analysis were carried out to determine the pollutant transportation paths and sources of the potential source area. The results show that air mass transportation mainly comes from three directions: northwest, northeast, and southwest China. The airflow in northwest China moves faster and cleaner, while the airflow from the northeast and southwest moves slowly and carries a high concentration of pollutants. PSCF and CWT analyses show that the critical potential sources are mainly located in this area and some cities next to the study area. This study has important practical significance for the environmental research of Chang-Zhu-Tan region and can provide theoretical reference for regional joint prevention and control of air pollution.
      PubDate: Fri, 25 Mar 2022 05:50:01 +000
  • The Influence of Work Zone Management on User Carbon Dioxide Emissions in
           Life Cycle Assessment on Highway Pavement Maintenance

    • Abstract: The higher contribution of traffic delay to environmental impacts is urging the highway agencies to take work zone management into the maintenance schemes decision-making. Aiming to understand the role of work zone management in user CO2 emissions reduction, this paper firstly developed a practical methodological framework of traffic delay-related CO2 emissions caused by highway maintenance based on a popular life cycle user cost analysis approach in regard of the microscopic vehicle operation analysis. The method was applied in an actual freeway flexible pavement with 15-year design life in Shaanxi Province, China, covering three types of preventive maintenance, correction maintenance, and rehabilitation. In addition, the impacts of key inputs of proposed method on work zone user CO2 emissions results were checked. The results show that traffic delay attributes to 29.4% of total CO2 emissions of the life cycle of highway pavement maintenance, and 51.8% of work zone user CO2 emissions result from preventive maintenance, especially from micro vehicle operations including speed change and queue near work zone (62% of total work zone user CO2 emissions). The work zone management alternative strategies related to less traffic volume or higher highway capacity including vehicle type limitation and the limited work zone speed have an advantage in reducing the work zone CO2 emissions over changing work zone length or work zone timing. The findings in this paper may present a useful tool and reference for robustly supporting the decision-making on highway maintenance carbon mitigation in work zone traffic.
      PubDate: Fri, 11 Mar 2022 08:35:01 +000
  • High Pollution Loadings Influence the Reliability of Himawari-8 Cloud-Mask
           in Comparison with Space-Based Lidar and Surface Observations

    • Abstract: Cloud identification methods of passive sensors are usually on the basis of different thresholds at different wavelengths. However, the high pollution levels may contribute to the misidentification of cloud mask of Advanced Himawari Imager (AHI) carried on Himawari-8. This study comprehensively analyses and demonstrates this possibility by comparing the AHI cloud-masks and space-based lidar observations based on surface observations of air-polluted loadings from January 1, 2016, to December 31, 2019. Therefore, this study comprehensively explores this impact by comparing the AHI cloud-masks and space-based lidar observations by using surface observations of air-polluted loadings from January 1, 2016, to December 31, 2019. Case studies that compare the two sensors indicate that the performance of AHI cloud detection is degenerative during aerosol events. Long-term statistical analysis demonstrates that the average hit ratio of clear (cloud) between the two sensors during the period is 79% (63%) and the consistency (hit rate) of cloud-mask between AHI and CALIOP decreases with increasing pollution levels. On the contrary, the low uncertainty ratios with 15% of cloud and 3% of clear exist in low PM2.5 levels (lower than 40 μg/m3), while the high uncertainty ratios with 47% of cloud and 15% of clear exist in high PM2.5 levels (higher than 130 μg/m3). Therefore, results demonstrate that the reliability of AHI cloud-mask is weakened by high air-polluted levels. Further improvement of AHI cloud-mask algorithm is desired because AHI products with high temporal resolution are vital in several related fields, such as climate change, aerosol-cloud interaction, and air-polluted mapping.
      PubDate: Sun, 27 Feb 2022 13:35:02 +000
  • Prediction of PM2.5 in an Urban Area of Northern Thailand Using
           Multivariate Linear Regression Model

    • Abstract: As a result of considerable changes in rural areas in Northern Thailand, the frequency and intensity of haze outbreaks from particulate pollution, particularly fine particulate matter (PM2.5), has increased in this region. To supplement ground-based monitoring where PM2.5 observation is limited, this study applied a multivariate linear regression model to predict PM2.5 concentrations in 2020 using aerosol optical depth (AOD); meteorological parameters of wind velocity, temperature, and relative humidity; and gaseous pollutants such as SO2, NO2, CO, and O3 from ground-based measurements at three locations: Chiang Mai, Lampang, and Nan provinces in Northern Thailand. Two multivariate linear regression models were conducted in this study. The first model (model 1) is a generic model with meteorological parameters of aerosol optical depth (AOD), temperature, relative humidity, and wind speed. The second model (model 2) includes meteorological parameters and several gaseous pollutants, such as SO2, NO2, CO, and O3. In general, the regression model, which used hourly data from 2020 of the three provinces, adequately characterized the PM2.5 concentrations. The performance of model 2 was good for the prediction of PM2.5 concentrations at Chiang Mai (R2 = 0.52) and Lampang (R2 = 0.60). Model 2 improved the prediction of PM2.5 concentration compared to model 1 for both wet and dry seasons. However, model uncertainties were also present, which lays a foundation for further study.
      PubDate: Tue, 22 Feb 2022 06:20:01 +000
  • Evaporation Rate Prediction Using Advanced Machine Learning Models: A
           Comparative Study

    • Abstract: Accurately estimating the amount of evaporation loss is necessary for scheduling and calculating irrigation water requirements. In this study, four machine learning (ML) modeling approaches, extreme learning machine (ELM), gradient boosting machine (GBM), quantile random forest (QRF), and Gaussian process regression (GPR), have been developed to estimate the monthly evaporation loss over two stations located in Iraq. Monthly climatical parameters have been used as an input variable for simulating the evaporation rate. Several statistical measures (e.g., mean absolute error (MAE), correlation coefficient (R), mean absolute percentage error (MAPE), and modified index of agreement (Md)), as well as graphical inspection, were used to compare the performances of the applied models. The results showed that the GBM model has much better performance in predicting monthly evaporation over two stations compared to other applied models. For the first case study which was in Diyala, the results showed a prediction enhancement in terms of MAE and RMSE by 7.17%, 21.01%; 16.51%, 15.74%; and 23.14%, 26.64%; using GBM compared to ELM, GPR, and QRF, respectively. However, for the second case study (in Erbil), the prediction enhancement was improved in terms of reduction of MAE and RMSE by 10.88%, 9.24%; 15.24%, 5%; and 16.06%, 15.76%; respectively, compared to ELM, GPR, and QRF models. The results of the proposed GMBM model can therefore assist local stakeholders in the management of water resources.
      PubDate: Mon, 21 Feb 2022 10:35:01 +000
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