Trend and Temporal Variability of Drought in Kirklareli Province Using Reconnaissance Drought Index and Standardized Precipitation Index by Mustafa Utku Yılmaz

“…The monthly precipitation and temperature data from the Kırklareli meteorological station between water years 1960-2021 were used to calculate the SPI and RDI. …”
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Comparison of Precipitation Rates from Global Datasets for the Five-Year Period from 2019 to 2023 by Heike Hartmann

“…Precipitation is a fundamental component of the hydrologic cycle and is an extremely important variable in meteorological, climatological, and hydrological studies. …”
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Assessing Hydropower Potential in Nepal’s Sunkoshi River Basin: An Integrated GIS and SWAT Hydrological Modeling Approach by Rinki Bhattarai, Binaya Kumar Mishra, Deepa Bhattarai, Dipendra Khatiwada, Pankaj Kumar, Gowhar Meraj

“…Topographical, soil, land use, meteorological, and discharge data were employed to assess the study area for the appropriateness of hydropower generation. …”
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Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil by Anibal Gusso, Damien Arvor, Jorge Ricardo Ducati, Mauricio Roberto Veronez, Luiz Gonzaga da Silveira

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Seasonal variation of different seminal parameters of breeding buffalo bulls by Hasan Riaz

“…Climatic data was also collected from the Regional Meteorological Center, Sahiwal, during the study period. …”
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A hybrid deep learning air pollution prediction approach based on neighborhood selection and spatio-temporal attention by Gang Chen, Shen Chen, Dong Li, Cai Chen

“…The complex nature of pollutant data is influenced by fluctuating meteorological conditions, diverse pollution sources, and propagation processes, underscores the crucial importance of the spatial and temporal feature extraction for accurately predicting air pollutant concentrations. …”
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Comparison of Satellite-based PM2.5 Estimation from Aerosol Optical Depth and Top-of-atmosphere Reflectance by Heming Bai, Zhi Zheng, Yuanpeng Zhang, He Huang, Li Wang

“…In this study, satellite observations of TOA reflectance and AOD from the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite in 2016 over Yangtze River Delta (YRD) and meteorological data are used to estimate hourly PM2.5 based on four different machine learning algorithms (i.e., random forest, extreme gradient boosting, gradient boosting regression, and support vector regression). …”
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Spaciotemporal distribution characteristics of glacial lakes and the factors influencing the Southeast Tibetan Plateau from 1993 to 2023 by Yu Mingwei, Guo Yonggang, Zhang Jian, Li Feng, Su Libin, Qin Deshun

“…Using Google Earth Engine (GEE) data in conjunction with meteorological data, this study examined the variation characteristics of glacial lakes in southeastern Tibet from 1993 to 2023. …”
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Correction of CAMS PM₁₀ Reanalysis Improves AI-Based Dust Event Forecast by Ron Sarafian, Sagi Nathan, Dori Nissenbaum, Salman Khan, Yinon Rudich

“…A correction model that links pixel-wise errors with atmospheric and meteorological variables was taught using gradient-boosting algorithms. …”
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Rural-urban transformation shapes oasis agriculture in Morocco’s High Atlas Mountains by Youness Boubou, Kira Fastner, Andreas Buerkert

“…Surveys on agricultural practices, census, and meteorological data were combined with GIS (Geographical Information System) -based analyses to examine land use and cropping pattern changes of 625 fields from 1967 to 2022. …”
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Extreme Air Pollution Events Spiking Ionic Levels at Urban and Rural Sites of Indo-Gangetic Plain by Manisha Mishra, U. C. Kulshrestha

“…These changes, which were corroborated by observations of the meteorological conditions, played an essential role in the wintertime atmospheric chemistry. …”
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Environmental consequences of oil and gas extraction on the example of the Bytkiv-Babchenskyi Oil and Gas Field by O. Mandryk, M. Orfanova, Yu. Hrybinyk, M. Stakh, V. Zaritskyi

“…The following methods were used: observation, measurement of environmental indicators, meteorological and physical field parameters, and laboratory analysis methods. …”
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Characteristics and mechanism of MBT anomaly of Karakum desert related with the Hindu Kush earthquake by Yifan Ding, Ziqing Wang, Yuan Qi, Wenfei Mao, Qiqi Zhang, Lixin Wu

“…Validating with multi-source auxiliary data such as surface temperature (ST), microwave polarization difference index (MPDI), soil moisture (SM), rainfall and snowfall, we confirmed the positive MBT anomaly appeared in the Karakum Desert from January 10 to January 13 was attributed to the seismic activity but not meteorological factors. The upward transfer of P-hole particles, activated in the deep hypocenter area by accumulated crustal stress during the pre-, co- and after-EQ period, to the Quaternary surface along the stress gradient, was believed to have reduced the local ground surface dielectric constant and amplified the microwave radiation, which leading subsequently to the positive MBT anomalies. …”
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Impacts of Chemical Initial Conditions in the WRF-CMAQ Model on the Ozone Forecasts in Eastern China by Tangyan Hou, Shaocai Yu, Yaping Jiang, Xue Chen, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Pengfei Li, Jianmin Chen, Xiaoye Zhang

“…The influences of different chemical initial conditions on the O3 forecasts are presented by using two sets of meteorological data (NCEP Final Operational Global Analysis [FNL] and Global Forecast System [GFS]) as initial conditions (IC) and boundary conditions (BC) to drive the WRF/CMAQ model. …”
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Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates by Siham Acharki, Ali Raza, Dinesh Kumar Vishwakarma, Mina Amharref, Abdes Samed Bernoussi, Sudhir Kumar Singh, Nadhir Al-Ansari, Ahmed Z. Dewidar, Ahmed A. Al-Othman, Mohamed A. Mattar

“…The FAO-56 Penman-Monteith (PM-FAO56) model, a widely endorsed approach for RET estimation, often encounters limitations due to the lack of complete meteorological data. This study evaluates the performance of eight empirical models and four machine learning (ML) models, along with their hybrid counterparts, in estimating daily RET within the Gharb and Loukkos irrigated perimeters in Morocco. …”
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Effect of Emission Penalty and Annual Interest Rate on Cogeneration of Electricity, Heat, and Hydrogen in Karachi: 3E Assessment and Sensitivity Analysis by Mehdi Jahangiri, Ali Mostafaeipour, Habib Ur Rahman Habib, Hamed Saghaei, Asad Waqar

“…To this end, 4500000 possible cases were analyzed, simulated, and optimized with the HOMER software using 20-year average meteorological data from the NASA website. A sensitivity analysis was performed on this system for the first time in Pakistan. …”
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Completion of the Central Italy daily precipitation instrumental data series from 1951 to 2019 by Gamal AbdElNasser Allam Abouzied, Guoqiang Tang, Simon Michael Papalexiou, Martyn P. Clark, Eleonora Aruffo, Piero Di Carlo

“…It is also an essential meteorological variable used as input for hydroclimatic models and projections. …”
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Adapting Ensemble‐Calibration Techniques to Probabilistic Solar‐Wind Forecasting by N. O. Edward‐Inatimi, M. J. Owens, L. Barnard, H. Turner, M. Marsh, S. Gonzi, M. Lang, P. Riley

“…Ensemble forecasting generates sets of outputs to create probabilistic forecasts which quantify forecast uncertainty, vital for reliable/actionable forecasts. We adapt meteorological methods to create a calibrated solar‐wind ensemble and probabilistic forecast for ambient solar wind, a prerequisite for accurate coronal mass ejection (CME) forecasting. …”
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A Study on Dust Storm Pollution and Source Identification in Northwestern China by Hongfei Meng, Feiteng Wang, Guangzu Bai, Huilin Li

“…The study found that PM₁₀ played a dominant role in the storm, and the AOD values during the storm in Lanzhou were significantly higher than the annual average, highlighting the severe impact on regional air quality. Key meteorological conditions influencing the storm’s occurrence were analyzed, including the formation and eastward movement of a high-potential ridge, convection driven by diurnal temperature variations, and surface temperature increases coupled with decreased relative humidity, which together promoted the generation and development of dust. …”
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The necessity of gestational vitamin D supplementation depends on ambient temperature: concern for infant vitamin D status by Wanjun Yin, Wanjun Yin, Wanjun Yin, Wanjun Yin, Lei Zhang, Lei Zhang, Peng Zhu, Peng Zhu

“…The daily mean temperature of Hefei was obtained from the China Meteorological Data Sharing Service System. Individual information on sociodemographic characteristics, perinatal health status, lifestyle, and birth outcomes was collected prospectively.ResultsThe best-fit relationship was observed in the regression model using a quadratic function to describe the association between the ambient temperature of the eighth gestational month (29–32 gestational weeks) and cord blood 25(OH)D concentrations (R2 = 0.358, p < 0.001). …”
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