Theoretical and Applied Climatology最新文献

{"title":"Sensitivity study of RegCM4.7 model to land surface schemes (BATS and CLM4.5) forced by MPI-ESM1.2-HR in simulating temperature and precipitation over Iran","authors":"Lobat Kosari Moghadam, N. Ghahreman, Iman Babaeian, P. Irannejad","doi":"10.1007/s00704-024-05135-x","DOIUrl":"https://doi.org/10.1007/s00704-024-05135-x","url":null,"abstract":"","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modified data classification for extreme values in Şen’s innovative trend analysis: A comparative trend study for the Aegean and Eastern Anatolia Regions of Türkiye","authors":"O. Asikoglu, Harun Alp, Ibrahim Temel","doi":"10.1007/s00704-024-05129-9","DOIUrl":"https://doi.org/10.1007/s00704-024-05129-9","url":null,"abstract":"","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of human activities on rainfall-runoff relationships at different time scales in the Minjiang River Basin","authors":"Kaili Geng, Xingwei Chen, Meiling Zheng, Yunpeng Gao, Zipeng Gu, Huaxia Yao","doi":"10.1007/s00704-024-05124-0","DOIUrl":"https://doi.org/10.1007/s00704-024-05124-0","url":null,"abstract":"","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of precipitation temporal distribution pattern of post-processed sub-daily ECMWF forecasts","authors":"Kousha Hoghoughinia, Bahram Saghafian, Saleh Aminyavari","doi":"10.1007/s00704-024-05134-y","DOIUrl":"https://doi.org/10.1007/s00704-024-05134-y","url":null,"abstract":"","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of atmospheric precipitable water vapour distribution and trend over India","authors":"Chander Singh Tomar, Rajeev Bhatla, Nand Lal Singh, Vivek Kumar, Pradeep Kumar Rai, Vijay Kumar Soni, Ram Kumar Giri","doi":"10.1007/s00704-024-05110-6","DOIUrl":"https://doi.org/10.1007/s00704-024-05110-6","url":null,"abstract":"<p>Integrated Precipitable Water Vapor (IPWV) wields significant influence over atmospheric processes, the climate system, and the hydrological cycle. Spatial and temporal variability characterizes water vapor distribution in the atmosphere, with equatorial regions registering elevated water vapor percentages. There are various types of instruments and methods to assess the quantity of moisture in the air. Global Navigation Satellite System (GNSS) and radiosonde techniques have been widely used to estimate IPWV in the atmosphere. European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-5) is the latest reanalysis IPWV dataset. This study aims to assess the congruence of ERA-5-derived IPWV with GNSS-derived IPWV and study the spatial and temporal variability of IPWV over Indian region. The IPWV data from 16 monitoring stations of GNSS Atmosphere Water Vapor Watch Network of the India Meteorological Department (IMD) have been compared with ERA-5 data. The IPWV data from GNSS and ERA-5 are in excellent agreement as corroborated by correlation coefficients spanning 0.97 to 1.00 and the Root Mean Square Error (RMSE) values varying between 1.5 mm and 5.6 mm. IPWV values exhibit prominent seasonal variations, with minimum values during the winter months and peak appears between June and September, aligning with warm and moist monsoon season of India. The ERA5 data from 1981 to 2020 were used to study variability and trend over Indian region. Strong positive correlations are observed between rainfall and IPWV. The results indicated IPWV trends are moistening especially over Indian landmass, the Indian Ocean, Arabian Sea and Bay of Bengal during all the seasons except winter.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141946991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drought variability in Pakistan: Navigating historical patterns in a changing climate with global teleconnections","authors":"Muhammad Latif, Hira Shireen, Shahzada Adnan, Rehan Ahmed, Abdelwaheb Hannachi","doi":"10.1007/s00704-024-05138-8","DOIUrl":"https://doi.org/10.1007/s00704-024-05138-8","url":null,"abstract":"<p>This study investigates the spatiotemporal variability of drought patterns in Pakistan on an annual timescale over 50 years (1971 – 2020) using six distinct drought indices [viz., Standardized Precipitation Index (SPI), Agricultural SPI, Reconnaissance Drought Index (RDI), Effective RDI, Deciles Index (DI), and Percentage Departure (PD)]. Empirical Orthogonal Function (EOF) analyses are employed on the SPI drought index to evaluate interannual variations in drought and their correlation with large-scale ocean–atmosphere circulation patterns. The magnitude of the trends is measured using the non-parametric Sen’s slope estimator, while their statistical significance is evaluated through the Mann–Kendall test. To further explore potential shifts in the correlations between the annual SPI and various climate indices, Rodionov’s regime shift detection test is applied. Our findings revealed six drought years: 1971, 2000, 2001, 2002, 2015, and 2018. The most intense and prolonged episode of drought, reaching an extreme category, occurred from 2000 to 2002, affecting over 60% of Pakistan’s total area. The leading EOF mode of the annual SPI demonstrates a robust relationship with the Pacific Decadal Oscillation (PDO). The second mode characterizes a significant Tropical Southern Atlantic (TSA) pattern, suggesting some level of predictability in drought occurrences across Pakistan. Moreover, regime shift analysis reveals two significant shifts: one in 2006 in the correlation between SPI and PDO, as well as Niño 3.4, and another in 2013 between SPI and TSA. This study can provide valuable insights for policymakers to develop climate-resilient agricultural and water resource management strategies, fostering sustainable development in drought-prone areas of the country.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141946989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Daily sunshine grids for Austria since 1961 – combining station and satellite observations for a multi-decadal climate-monitoring dataset","authors":"Johann Hiebl, Quentin Bourgeois, Anna-Maria Tilg, Christoph Frei","doi":"10.1007/s00704-024-05103-5","DOIUrl":"https://doi.org/10.1007/s00704-024-05103-5","url":null,"abstract":"<p>Grid datasets of sunshine duration at high spatial resolution and extending over many decades are required for quantitative applications in regional climatology and environmental change (e.g., modelling of droughts and snow/ice covers, evaluation of clouds in numerical models, mapping of solar energy potentials). We present a new gridded dataset of relative (and derived absolute) sunshine duration for Austria at a grid spacing of 1 km, extending back until 1961 at daily time resolution. Challenges in the dataset construction were consistency issues in the available station data, the scarcity of long time series, and the high variation of cloudiness in the study region. The challenges were addressed by special efforts to correct evident breaks in the station series and by adopting an analysis method, which combines station data with satellite data. The methodology merges the data sources non-contemporaneously, using statistical patterns distilled over a short period, which allowed involving satellite data even for the early part of the study period. The resulting fields contain plausible mesoscale structures, which could not be resolved by the station network alone. On average, the analyses explain 47% of the spatial variance in daily sunshine duration at the stations. Evaluation revealed a slight systematic underestimation (− 1.5%) and a mean absolute error of 9.2%. The average error is larger during winter, at high altitudes, and around the 1990s. The dataset exhibits a conditional bias, which can lead to considerable systematic errors (up to 15%) when calculating sunshine-related climate indices.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141946990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of the reliability to use NASAPOWER gridded weather applied to irrigation planning and management in Brazil","authors":"Rafael Battisti, Otávio Coscrato Cardoso da Silva, Fábio Miguel Knapp, José Alves Júnior, Marcio Mesquita, Leonardo Amaral Monteiro","doi":"10.1007/s00704-024-05113-3","DOIUrl":"https://doi.org/10.1007/s00704-024-05113-3","url":null,"abstract":"<p>The sustainability of irrigated agricultural systems depends on the water use efficiency based on management. The efficiency is reach first by an adequate estimation of crop water demand. However, the lack of weather data is a limitation to plan and estimation irrigation demand in Brazil. This way, the aim of this study was to investigate NASAPOWER gridded system as alternative source of weather data in Brazil. First, we tested how reliable are the meteorological variables between NASAPOWER and ground weather stations. Further, we calculated the maximum number of consecutive dry days within the crop cycle, and the irrigation demand through the soil-crop water balance for nine crops. The performance was investigated through coefficients of determination (r²), agreement (d) and normalized root mean square error (nRMSE). In general, air temperature and incoming solar radiation presented the best statistical metrics (r² ~ 0.53–0.83; d ~ 0.84–0.94; and nRMSE ~ 8.61–23.5%), whereas the wind speed had the worst (r² ~ 0.09; d ~ 0.53; and nRMSE ~ 93%). NASAPOWER figured as a valuable tool for determine the number of dry days and number of irrigation events during the crop cycle. Irrigation demand showed a good relation between NASAPOWER and ground weather station (r² = 0.79 and d = 0.94), but with nRMSE of 53%, due to a higher deviation when irrigation demand is above 200 mm cycle^− 1. NASAPOWER showed potential as source of meteorological information for irrigation management for different cropping systems, where local adjustment could improve performances for crops with long cycle.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unusual inland intrusion of nocturnal sea breeze in the North China plain during summer","authors":"Xun Hu, Xuhui Cai, Yujie Cai, Xuesong Wang, Yu Song, Xiaobin Wang, Ling Kang, Hongsheng Zhang","doi":"10.1007/s00704-024-05131-1","DOIUrl":"https://doi.org/10.1007/s00704-024-05131-1","url":null,"abstract":"<p>A month-long numerical simulation investigates summertime sea breezes in the North China Plain (NCP), occurring predominantly from late afternoon to night-time and penetrating over 100 km inland. The key factor driving this phenomenon is identified as a persistent lee-side cyclone in the western NCP, formed by dynamic interactions between upper-air north-westerly winds and mountain barriers upstream. Throughout a summer month, the lee-side cyclone varies in strength diurnally, significantly influencing sea breeze development. A case study of high-resolution simulation provides detailed insights into the wind field and the evolving lee-side cyclone structure. In the evening peak, three sectors of air flows—westerly, southerly, and south-easterly—encompass the cyclone core, demarcated by fronts with sharp gradients in temperature, moisture, and wind speed and direction. As the south-easterly sea breeze intensifies, it swiftly advances inland along the mountainside, forming an arch-like intrusion path. With the weakening and south-westward movement of the lee-side cyclone, the sea breeze transforms into an inertial current, guided further south-westward. The vertical structure of the sea breeze is revealed, including the depth of its moisture-layer and its uplifting effect on the warmer inland air mass at the cyclone core. The interaction between the lee-side cyclone and sea breeze facilitates the transport of substantial water vapor from the Bohai Sea coastline to the interior of the NCP. These findings provide new insights into the summertime sea breeze mechanism in the NCP, with implications for local weather patterns, water vapor budget, and air pollutant transport.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling of irrigation water quality parameter (sodium adsorption ratio) using hybrid swarm intelligence-based neural networks in a semi-arid environment at SMBA dam, Algeria","authors":"Mohammed Achite, Okan Mert Katipoğlu, Nehal Elshaboury, Veysi Kartal, Gaye Aktürk, Neşe Ertugay","doi":"10.1007/s00704-024-05109-z","DOIUrl":"https://doi.org/10.1007/s00704-024-05109-z","url":null,"abstract":"<p>Sodium adsorption rate (SAR), which significantly affects soil and plant health, is determined according to the concentration of sodium ions, calcium, and magnesium in irrigation water. Accurate estimation of SAR values is vital for agricultural production and irrigation. In this study, hybrid swarm intelligence-based neural networks are used to model sodium adsorption ratio in irrigation water quality parameters in a semi-arid environment at Sidi M’Hamed Ben Aouda (SMBA) dam, Algeria. For this, the nature-inspired optimization techniques of particle swarm optimization (PSO), genetic algorithm (GA), Jaya algorithm (JA), artificial bee colony (ABC), and firefly algorithm (FFA) and the signal processing technique of variational mode decomposition (VMD) have been combined with artificial neural networks (ANN). Correlation matrices were used to select the data entry structure in the established models. Water quality parameters with a statistically significant and medium to high relationship with SAR values were presented as input to the model. The overall performance was measured using various statistical metrics, scatter diagrams, Taylor diagrams, correlograms, boxplots, and line plots. In addition, the effect of input parameters on model estimation was evaluated according to Sobol sensitivity analysis. As a result, the GA-ANN algorithm demonstrated superior performance (MSE = 0.073, MAE = 0.193, MAPE = 0.048, MBE=-0.16, R² = 0.934, WI = 0.968, and KGE = 0.866) based on the statistical indicators, indicating better results compared to other models. The second-best model, ABC-ANN (MSE = 0.084, MAE = 0.233, MAPE = 0.066, MBE=-0.135, R² = 0.897, WI = 0.965, and KGE = 0.920) was also selected. The weakest prediction outputs were obtained from the VMD-ANN model. The accurate and reliable estimation of SAR in irrigation water has the potential to facilitate improvements in agricultural irrigation management and agricultural production efficiency for farmers, agricultural practitioners, and policymakers.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}