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1
AHMED, F. K., and A. MOBASSHER. "An investigation of monthly mean maximum and absolute maximum temperatures of Bangladesh." MAUSAM 42, no. 4 (2022): 361–66. http://dx.doi.org/10.54302/mausam.v42i4.3267.
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Using synoptic and climatological data for 27 years (1951-1977) of 16 stations of Bangladesh, temporal and spatial variations of the ab3olute maximum temperature of Bangladesh have been studied. Empirical probabilities for the interval 35.loC-40.o0C and 40,1° -45.0°C of absolute maximum temperature have been examined. Some correlation characteristics between some pairs of station for some selected months have been analysed. An attempt has been made to explain the cause of temporal and spatial variations of maximum and absolute maximum temperatures from the point of view of synoptic meteorology.
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MOBASSHER, A., MD AMINUR ISLAM, and SOPAN DAS. "Some climatological characteristics of the changing pattern of temperature in Bangladesh – A diagnostic approach." MAUSAM 67, no. 2 (2021): 441–54. http://dx.doi.org/10.54302/mausam.v67i2.1350.
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Based on climatological data of maximum and minimum temperatures of seventeen stations for a period of 60 years (1949 - 2008), obtained from Bangladesh Meteorological Department (BMD), the changing pattern of temperature in Bangladesh has been investigated. Some characteristics of annual variation and spatial distribution of mean monthly minimum, mean monthly maximum and mean monthly temperature, annual variation and spatial distribution of mean monthly amplitude of temperature have been explained. The characteristics of changing pattern of temperature such as standard deviation, coefficient of variation, ratio between mean monthly maximum and mean monthly minimum temperatures have been studied. The run of the temperature in different stations for the years 1949-2008, the periodicity of mean annual temperature and mean decade deviations have been discussed. The integral curve of mean annual temperature for Dhaka has been prepared and explained. Regression analysis for mean monthly temperature of January, April, July and October for the stations Sylhet, Chittagong, Khulna and Rangpur with Dhaka have been analyzed. Some linear correlation equations have been deduced. In the investigation, attempts (as far as possible) have been made to explain the synoptic cause of the changing pattern of temperature in Bangladesh.
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Овсепян, Азатуи А., Анаит Н. Хлгатян, Рима А. Аветисян, Ваагн С. Мурадян та Шушаник Г. Асмарян. "ДИСТАНЦИОННОЕ ЗОНДИРОВАНИЕ ТЕМПЕРАТУРЫ ПОВЕРХНОСТИ ВОДЫ ОЗЕРА СЕВАН С ПРИМЕНЕНИЕМ ДАННЫХ COPERNICUS GLOBAL LAND SERVICE". Proceedings of the YSU C: Geological and Geographical Sciences 57, № 3 (261) (2023): 255–63. http://dx.doi.org/10.46991/pysu:c/2023.57.3.255.
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Water surface temperature is an important factor influencing the ecological state of the lake. Remote sensing techniques are an important tool for obtaining lake surface water temperature, which provides periodic information from the entire surface of the lake. The aim of this study is to analyze the spatiotemporal change of Lake Sevan surface water temperature based on remote sensing data and to analyze the relationship between the surface temperature of the lake water and the air temperature of the lake basin. The results confirm the relationship between the water surface temperature of Lake Sevan and the air temperature in the lake basin. Under conditions of reliability p<0.01, the following correlation results were obtained: between average ten-day water surface temperatures and ten-day air temperatures with coefficient r=0.929, between average monthly water surface temperatures and monthly maximum air temperatures with coefficient r=0.918, between the monthly maximum water surface temperature and the monthly maximum air temperature with a coefficient of r=0.961. Analysis of remote sensing data shows both patterns and anomalous behavior of lake surface water temperature.
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Wang, Shunjiu. "Variations in Maximum and Minimum Temperature in Mount Qomolangma during 1971–2020." Atmosphere 15, no. 3 (2024): 358. http://dx.doi.org/10.3390/atmos15030358.
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Based on the daily maximum and minimum temperature observational data during 1971–2020, the variabilities of the maximum and minimum temperature of Mount Qomolangma are analyzed. The daily maximum temperature is 25.8 °C and the daily minimum temperature is −31.4 °C during the study period in Mount Qomolangma. Overall, there has been an upward trend with decadal laps for both maximum and minimum temperature. On monthly, seasonal, and annual scales, neither maximum temperature nor minimum temperature time series exhibit an increasing trend from 1971 to 2020. The increasing trends in monthly minimum temperature are even more pronounced than those in maximum temperature. Abrupt changes are noted in both monthly, seasonal, and annual maximum and minimum temperature time series. Specifically, an abrupt change in annual maximum temperature occurred in the 1980s, while an abrupt change in annual minimum temperature occurred in the 1990s. Differences between the north and south slope of Mount Qomolangma are evident, with temperature fluctuations of the north slope being more extreme than those of south slope. The seasonal and annual maximum temperature of the north slope is higher than that of the south slope, except for winter, and the seasonal and annual minimum temperatures of the north slope are all lower than those of the south slope. The tendences of maximum and minimum temperatures in the north slope are more dominant than those in the south slope. The findings are beneficial for understanding the characteristics of local climate change on the Tibetan plateau and to underscore the significant role of Mount Qomolangma in the context of global warming.
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Jahan, Md Sarwar, Sanjida Akter Nishita, Afifa Tamim, and S. M. Abdullah Al Mamun. "ANALYSIS OF TEMPERATURE TREND IN KHULNA DISTRICT OF BANGLADESH." Environment & Ecosystem Science 8, no. 2 (2024): 134–42. https://doi.org/10.26480/ees.02.2024.134.142.
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This study examines the trends in monthly maximum, minimum, and average temperatures over a 20-year period (2003-2022) in Khulna district, Bangladesh. The temperature data were sourced from the Regional Inspection Center (R.I.C) of the Bangladesh Meteorological Department, Gollamary, Khulna. The aim was to assess temperature deviations in the district over time. Using linear trend analysis, long-term temperature changes were evaluated. The annual mean maximum, minimum, and average temperatures showed increasing trends when plotted against the years, though the year-to-year variability was not statistically significant. The regression equations obtained for maximum, minimum, and average temperatures were: (y = 0.0251x – 19.006, R² = 0.1525), (y = 0.0177x – 8.789, R² = 0.1492), and (y = 0.0098x + 2.5477, R² = 0.0476), respectively. A bimodal dispersion pattern was observed across all three temperature aspects throughout the months during 2003-2022. Monthly temperatures (maximum, minimum, and average) did not follow a consistent pattern, as shown by the linear regression analysis, with both increasing and decreasing trends identified over the two decades. May was found to be the warmest month, while January was the coldest when considering mean monthly maximum and average temperatures. Furthermore, the highest upsurge in mean monthly average temperature was recorded in July (0.05390C), while the bulk reduction was detected in February (0.03670C). Principal component analysis indicated that the first two components accounted for 93% of the total variation. The study recommends further temperature monitoring methods due to observed instability in temperature.
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Hughes, Gillian L., Suhasini Subba Rao, and Tata Subba Rao. "Statistical analysis and time-series models for minimum/maximum temperatures in the Antarctic Peninsula." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463, no. 2077 (2006): 241–59. http://dx.doi.org/10.1098/rspa.2006.1766.
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It is now widely known that Antarctic air is warming faster than the rest of the world, and the Antarctic Peninsula has experienced major warming over the last 50 years. The monthly mean near surface temperature at the Faraday/Vernadsky station has increased considerably, at a rate of 0.56°C per decade over the year and at 1.09°C per decade over the winter. The increase is not the same over all the stations in the Antarctic region, and the increase is very significant at the Faraday/Vernadsky station. Only at this station are the minimum/maximum monthly temperatures, for the period 1951–2004, separately available, and we believe that the increase in mean surface temperature at this station is mainly due to the increases in minimum temperatures. Therefore, our object in this paper is to study the variations in the minimum/maximum temperatures using a multiple regression model with non-Gaussian correlated errors. By separately analysing the minimum and maximum temperatures, we could clearly identify the source of increase. The average temperature (usually calculated as (max+min)/2) smooths out any variation, and may not be that informative. We model the correlated errors using a linear autoregressive moving average model with innovations, which have an extreme value distribution. We describe the maximum-likelihood estimation methodology and apply this to the datasets described earlier. The methods proposed here can be widely used in other disciplines as well. Our analysis has shown that the increase in the minimum monthly temperatures is approximately 6.7°C over 53 years (1951–2003), whereas we did not find any significant change in the maximum temperature over the same period. We also establish a relationship between the minimum monthly temperatures and ozone levels, and use this model to obtain monthly forecasts for the year 2004 and compare it with the true values available up to December 2004.
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Christy, John R. "Monthly Temperature Observations for Uganda." Journal of Applied Meteorology and Climatology 52, no. 10 (2013): 2363–72. http://dx.doi.org/10.1175/jamc-d-13-012.1.
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AbstractThe International Surface Temperature Initiative is a worldwide effort to locate weather observations, digitize them for public access, and attach provenance to them. As part of that effort, this study sought documents of temperature observations for the nation of Uganda. Although scattered reports were found for the 1890s, consistent record keeping appears to have begun in 1900. Data were keyed in from images of several types of old forms as well as accessed electronically from several sources to extend the time series of 32 stations with at least 4 yr of data back as far as data were available. Important gaps still remain; 1979–93 has virtually no observations from any station. Because many stations were represented by more than one data source, a scheme is described to extract the “best guess” values for each station of monthly averages of the daily maximum, minimum, and mean temperature. A preliminary examination of the national time series indicates that, since the early twentieth century, it appears that Uganda experienced essentially no change in monthly-average daily maximum temperature but did experience a considerable rise in monthly-average daily minimum temperature, concentrated in the last three decades. Because there are many gaps in the data, it is hoped that readers with information on extant data that were not discovered for this study will contact the author or the project so that the data may be archived.
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Yehia, Mohamed A., Osama T. Al-Taai, and Morwa K. Ibrahim. "Spatiotemporal Distribution of Minimum-Maximum Temperature over Iraq for the Period (1980-2017)." IOP Conference Series: Earth and Environmental Science 1060, no. 1 (2022): 012026. http://dx.doi.org/10.1088/1755-1315/1060/1/012026.
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Abstract Climate behavior study analysis of the values of the famous temperature variables for each of the (minimum and maximum) temperatures that were studied in four main stations in Iraq (Mosul, Baghdad, Rutbah, Basra) during the period 1980-2017. The research aims to know the increase in the monthly rates of minimum and maximum temperature values and their impact on global warming, as the data were taken from satellites registered by the European Center for Medium-Range Weather Forecasts (ECMWF). Mann-Kendall statistical tests were used to calculate the important trends in the minimum and maximum temperature rates for each of the four previously mentioned stations. The results showed that there is a noticeable increase in the monthly average of minimum and maximum temperatures and that the general behavior of the trend of minimum and maximum temperatures tends to rise in its values in all regions of Iraq.
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Queiroz, Túlio Barroso, Cristian Rodrigo Montes, and Otávio Camargo Campoe. "A New Method to Calibrate Cardinal Temperatures for Eucalyptus Plantation." Forests 14, no. 8 (2023): 1631. http://dx.doi.org/10.3390/f14081631.
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Developing a good understanding of the interactions between forest plantation growth and climate is essential for predicting the impact of climate change on terrestrial ecosystems and for assessing the adaptation and vulnerability of tree species. One such interaction, the response in growth rate of a forest stand to changes in temperature, may be described mathematically. Some models that run on monthly time steps assume a yearly optimum, minimum, and maximum temperature for simplicity, which may not represent well to actual forest growth. Here, we developed a finer-resolution methodology that encompasses monthly growth rates and temperature limits to calibrate the parameters for an envelope curve in Eucalyptus plantations in South America. Several polynomial curves were tested to determine temperature patterns, and their yearly tree growth patterns demonstrated that responses to temperature differed by as much as 10 °C among seasons. The best curve was a second-degree polynomial curve, whose extreme values indicated the optimum temperature and whose real roots limited the minimum and maximum temperatures for growth. This polynomial was fitted every month to describe yearly changes in optimum, maximum, and minimum temperatures. When fitted to annual data, it determined 7 °C, 19 °C, and 31 °C as the minimum, optimum, and maximum temperatures for tree growth, respectively. The monthly model predictions indicated that the minimum, optimum, and maximum temperatures lay between 8 °C and 16 °C, 18 °C and 22 °C, and 27 °C and 30 °C, respectively. These monthly temperature ranges can improve the estimation of productivity in process-based models. Our results contribute to the understanding of tree growth dynamics and its relationship to changes in temperature. Accurate ranges of temperature can be used to improve productivity predictions in new expanding planting regions with no previous information or to suggest a regionalization for potential species.
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Nasher, NM Refat, and MN Uddin. "Maximum and Minimum Temperature Trends Variation over Northern and Southern Part of Bangladesh." Journal of Environmental Science and Natural Resources 6, no. 2 (2015): 83–88. http://dx.doi.org/10.3329/jesnr.v6i2.22101.
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Temperature is one of the pivotal climatic variables in our world climate literature. In the present study monthly, seasonal and yearly highest maximum and lowest minimum temperatures of two cities were analyzed. Mann-Kendall test and Sens Slope Estimator were used to determine the trend and slope magnitude. Chittagong, as the coastal city and Rajshahi, as Barind track were selected as a study area due to its respective geographical location. Such types of data of 52 years for Chittagong as well as 48 years for Rajshahi were collected from Bangladesh Meteorological Department (BMD). Monthly highest maximum and lowest minimum temperature data from 1950-2002 for Chittagong and 1964-2012 for Rajshahi were used for analysis. In Rajshahi, significant rising trends were found in highest maximum post-monsoon temperature, lowest minimum monsoon temperature and highest maximum temperature from July to October, June and August for lowest minimum temperature. Falling trends were found in annual highest maximum and lowest minimum temperatures, pre-monsoon highest maximum temperature, lowest minimum winter temperature and January lowest minimum temperature. For Chittagong, significant increasing trends found in post-monsoon highest maximum temperature, June to December highest maximum temperature except July and December lowest minimum temperature. No significant decreasing trend was found in Chittagong.DOI: http://dx.doi.org/10.3329/jesnr.v6i2.22101 J. Environ. Sci. & Natural Resources, 6(2): 83-88 2013
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Shouzhang, Peng. "High-spatial-resolution monthly temperatures dataset over China during 1901–2017." Earth System Science Data 11, no. 4 (2019): 1931–46. https://doi.org/10.5281/zenodo.3185722.
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The dataset with 0.5 arcminute (~1 km) was spatially downscaled from CRU TS v4.02 based on Delta downscaling method, including monthly minimum, maximum, and mean temperatures from 1901.1 to 2017.12. The dataset covers the main land area of China. The dataset was evaluated by 496 national weather stations across China, and the evaluation indicated that the downscaled dataset is reliable for the investigations related to climate change across China. Another data download site is Loess plateau Scientific Data Center (http://loess.geodata.cn/). This is a Chinese website. This website publishes the updated histrorical dataset and future downscaled monthly temperatures under multiple SSP Scenarios and GCMs, with 1 km spatial resolution. /*************/ The dataset is updated yearly. Now, the period of the dataset is from 1901.1 to 2020.12. /*************/ The future 1km dataset from 2021-2100 is published. The data provider recommended the below publication as the reference. Peng Shouzhang, Ding Yongxia, Liu Wenzhao, Li Zhi. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth System Science Data, 2019, 11, 1931–1946, https://doi.org/10.5194/essd-11-1931-2019.
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Seginer, Ido, and Bryan M. Jenkins. "Temperature exposure of greenhouses from monthly means of daily maximum and minimum temperatures." Journal of Agricultural Engineering Research 37, no. 3-4 (1987): 191–208. http://dx.doi.org/10.1016/s0021-8634(87)80017-3.
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Petropoulos, Zoe E., Oriana Ramirez-Rubio, Madeleine K. Scammell, et al. "Climate Trends at a Hotspot of Chronic Kidney Disease of Unknown Causes in Nicaragua, 1973–2014." International Journal of Environmental Research and Public Health 18, no. 10 (2021): 5418. http://dx.doi.org/10.3390/ijerph18105418.
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An ongoing epidemic of chronic kidney disease of uncertain etiology (CKDu) afflicts large parts of Central America and is hypothesized to be linked to heat stress at work. Mortality rates from CKDu appear to have increased dramatically since the 1970s. To explore this relationship, we assessed trends in maximum and minimum temperatures during harvest months between 1973 and 2014 as well as in the number of days during the harvest season for which the maximum temperature surpassed 35 °C. Data were collected at a weather station at a Nicaraguan sugar company where large numbers of workers have been affected by CKDu. Monthly averages of the daily maximum temperatures between 1996 and 2014 were also compared to concurrent weather data from eight Automated Surface Observing System Network weather stations across Nicaragua. Our objectives were to assess changes in temperature across harvest seasons, estimate the number of days that workers were at risk of heat-related illness and compare daily maximum temperatures across various sites in Nicaragua. The monthly average daily maximum temperature during the harvest season increased by 0.7 °C per decade between 1973 and 1990. The number of days per harvest season with a maximum temperature over 35 °C increased by approximately five days per year between 1974 and 1990, from 32 days to 114 days. Between 1991 and 2013, the number of harvest days with a maximum temperature over 35 °C decreased by two days per year, and the monthly average daily maximum temperature decreased by 0.3 °C per decade. Comparisons with weather stations across Nicaragua demonstrate that this company is located in one of the consistently hottest regions of the country.
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Petropoulos, Zoe E., Oriana Ramirez-Rubio, Madeleine K. Scammell, et al. "Climate Trends at a Hotspot of Chronic Kidney Disease of Unknown Causes in Nicaragua, 1973–2014." International Journal of Environmental Research and Public Health 18, no. 10 (2021): 5418. https://doi.org/10.3390/ijerph18105418.
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An ongoing epidemic of chronic kidney disease of uncertain etiology (CKDu) afflicts large parts of Central America and is hypothesized to be linked to heat stress at work. Mortality rates from CKDu appear to have increased dramatically since the 1970s. To explore this relationship, we assessed trends in maximum and minimum temperatures during harvest months between 1973 and 2014 as well as in the number of days during the harvest season for which the maximum temperature surpassed 35 °C. Data were collected at a weather station at a Nicaraguan sugar company where large numbers of workers have been affected by CKDu. Monthly averages of the daily maximum temperatures between 1996 and 2014 were also compared to concurrent weather data from eight Automated Surface Observing System Network weather stations across Nicaragua. Our objectives were to assess changes in temperature across harvest seasons, estimate the number of days that workers were at risk of heat-related illness and compare daily maximum temperatures across various sites in Nicaragua. The monthly average daily maximum temperature during the harvest season increased by 0.7 °C per decade between 1973 and 1990. The number of days per harvest season with a maximum temperature over 35 °C increased by approximately five days per year between 1974 and 1990, from 32 days to 114 days. Between 1991 and 2013, the number of harvest days with a maximum temperature over 35 °C decreased by two days per year, and the monthly average daily maximum temperature decreased by 0.3 °C per decade. Comparisons with weather stations across Nicaragua demonstrate that this company is located in one of the consistently hottest regions of the country.
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王, 文炯. "The Prediction of Monthly Maximum Temperature Based On Factor Decomposition." Advances in Applied Mathematics 10, no. 05 (2021): 1411–17. http://dx.doi.org/10.12677/aam.2021.105150.
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Costa, Rafaela Lisboa, Fabrício Daniel dos Santos Silva, Gabriel Fonseca Sarmanho, and Danielle Barros Ferreira. "Análise de Tendências de Precipitações e Temperaturas Mensais de 1961 a 2008 no Brasil Usando Dados Gradeados (Analysis of Trends of Monthly Precipitation and Temperatures of 1961 to 2008 in Brazil Using Gridded Data)." Revista Brasileira de Geografia Física 5, no. 5 (2013): 1227. http://dx.doi.org/10.26848/rbgf.v5i5.232917.
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Este trabalho analisa um conjunto climatológico de dados gradeados de precipitação, temperaturas médias, máximas e mínimas, mensais, de 1961 e 2008. Tendências lineares foram estudadas, identificando-se as áreas onde foram estatisticamente significantes. Tendências positivas, foram verificadas para temperaturas máximas, mínimas e médias, em diferentes intensidades. Em relação à precipitação, as áreas com tendências de aumento ou diminuição alternam-se mês a mês, com padrões menos evidentes do que os das temperaturas.Palavras-chave: temperatura, precipitação, tendências climáticas. Analysis of Trends of Monthly Precipitation and Temperatures of 1961 to 2008 in Brazil Using Gridded Data ABSTRACTThis paper analyzes a climatological dataset of monthly grid data of precipitation, average temperature, maximum and minimum temperature, between 1961-2008. Linear trends were studied, identifying the areas where these were statistically significant. Positive trends were observed for maximum, minimum and average temperatures, with different intensities. For precipitation, the areas with increasing or decreasing trend alternate month by month, with patterns less evident than the temperatures.Keywords: temperature, precipitation, climatic trends
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K. Shathir, Adnan, Layla Ali Mohammed Saleh, and Sumayah Amal Al-Din Majeed. "Forecasting Monthly Maximum Temperatures in Kerbala Using Seasonal ARIMA Models." Journal of University of Babylon for Engineering Sciences 27, no. 2 (2019): 223–32. http://dx.doi.org/10.29196/jubes.v27i2.2341.
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Weather forecasting is an important issue in meteorology and scientific research.In this research, the Seasonal Auto Regressive.Integrated Moving Average.(ARIMA) model which is based on Box-Jenkins method was adopted to build the forecasting model. The max. Monthly temperature data for Kerbala city for the period (Jan.1980 to Dec.2016) was employed. The autocorrelation and partial autocorrelation functions for time series data from years 1980 to 2015 were used to identify the most appropriate orders of the ARIMA models. The validation test of these models were performed using the monthly max. Temperature of the year 2016. To calculate the model's accuracy and compare among them, statistical criteria such as MAE, RMSE, MAPE, and R2 were used. The model (2, 1, 2) × (1, 1, 1)12 gave the most accurate results and used to forecast the monthly max. Temperature for the period (2017 to 2021) for study region.
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Putri, Jamiatul Khairunnisa, Suhadi, Muhammad Irfan, Hamdi Akhsan, and Iskhaq Iskandar. "Variability of Temperature Extreme Observes in Kalimantan." Jurnal Penelitian Pendidikan IPA 10, no. 11 (2024): 8734–44. https://doi.org/10.29303/jppipa.v10i11.9048.
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This study aims to analyze the trend of extreme temperatures in Kalimantan over the past few decades. The data used are daily temperatures from meteorological stations in West Kalimantan, Central Kalimantan, and South Kalimantan, with an observation period of January 1985 to December 2022. The research methodology involves four main stages: data collection, extreme temperature index calculation, trend detection, and correlation analysis with ENSO and IOD. The results showed an increasing trend in extreme temperatures (warming). The increase in mean annual maximum temperature (TXmean) ranged from 0.03°C to 2°C per century, while the mean annual minimum temperature increased from 0.2°C to 0.5°C per century. Monthly maximum value of daily max temperature (TXx) the increasing trend ranged from 0.19°C to 1.7°C, monthly maximum value of daily min temperature (TNx) increased from 0.1°C to 0.5°C. The monthly mean difference between daily max and min temperature (DTR) also shows an increase of 0.5°C to 1.7°C. This trend indicates that daytime (TXmean, TXx) and nighttime (TNmean, TNx) conditions in Kalimantan, especially in West, Central, and South Kalimantan, are getting hotter, with the daytime experiencing a more significant increase in temperature. The correlation between the extreme temperature index and ENSO and IOD is negative and positive, indicating that ENSO and IOD do not fully influence the increase in extreme temperatures. These findings have important implications for disaster mitigation planning and adaptation to climate change in the Kalimantan region.
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Samuel, Njipouakouyou, and Ali Mahamat Nour. "Modelling Monthly and Annual Trends of the Monthly Air Maximum Temperature in Ndjamena, Chad, Over the Climatic Period 1961-1990." Current Journal of Applied Science and Technology 42, no. 31 (2023): 34–46. http://dx.doi.org/10.9734/cjast/2023/v42i314215.
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The present article models monthly and annual trends of the monthly air maximum temperature in Ndjamena over the climatic period from 1961 to 1990. Monthly mathematical mean values over the period of this parameter has been calculated with their corresponding standard deviations. High values were registered from March to June, the beginning of the rainy season in the locality, and low values – during the dry season, from December to February. Its interval of variation was from 32.3°C in January to 41.0°C in April. Concerning the standard deviation, its interval of variation was from 0.9°C in April to 1.8°C in January, February and December. Deviations of the monthly air maximum temperatures from their corresponding mathematical mean values were calculated for each month over the climatic period. Their time trends were modeled by the least squares method. Analysis of the configuration their clouds of points in rectangular coordinates systems has shown that all monthly trends were according to the linear relationship. The coefficients of the obtained regression lines were mostly 0.1. This low value indicates that the time trend of the air maximum temperature was not significant to produce notable impacts on the environment in the considered locality. Similar treatments were applied to annual trends. The results were qualitatively the same. Thus, it is obviously clear during this climatic period no thermal perturbations to bring significant impacts to the environment were observed. But the study has revealed a weak tendency to the rise of the maximum air temperature in Ndjamena, particularly by the end of the period.
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Tiba, Chigueru, and Raquel Ghini. "Numerical procedure for estimating temperature in solarized soils." Pesquisa Agropecuária Brasileira 41, no. 3 (2006): 533–37. http://dx.doi.org/10.1590/s0100-204x2006000300023.
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The objective of this work was to develop a simplified numerical procedure for the estimation of accumulated monthly hours of solarized soil temperatures. The proposed model requires monthly means of daily solar radiation and maximum air temperature as input data, and a daily pattern of temperature variation assumed to be sine-shaped. The procedure was verified using observations made during the years 1992 and 1993 in Jaguariúna, SP. The proposed procedure can predict monthly temperature hours at 10 cm depth in the solarized soil, with acceptable accuracy, in the region for which it was developed.
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AUCAHUASI-ALMIDON, ANDREA, CARLOS CABRERA-CARRANZA, and JORGE GARATE-QUISPE. "Trend analysis and change-point detection of temperature and rainfall in southern Peruvian Amazon and its relation to deforestation." Journal of Agrometeorology 26, no. 4 (2024): 425–30. https://doi.org/10.54386/jam.v26i4.2687.
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The study aimed to identify the change points, tendencies, and trends in climatic parameters (precipitation and temperatures) and to investigate their relationship with deforestation in the southeastern Peruvian Amazon (Tambopata). Rainfall and temperature data for the Puerto Maldonado station from 1970 to 2023 was used. Monthly, seasonal, and annual precipitation as well as temperature (maximum, minimum, and mean) were analyzed for possible trends using nonparametric Mann-Kendal statistic test, while the Pettitt test was employed to detect the abrupt change point in time series. The Spearman's correlation coefficient was used to identify the relationship between deforestation and climate parameters. The results revealed a rise in mean, minimum, and maximum temperatures. Mann Kendall and Sen’s slope revealed significant trends in the monthly, seasonal and annual temperatures in the study period. However, in contrast to the temperature variation trend, the monthly, seasonal and annual precipitation did not present a significant trend. Significant positive correlations were obtained between deforestation and temperatures but its association with precipitation was not significant.
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Phumkokrux, Nutthakarn, and Somkamon Rukveratham. "Investigation of mean monthly maximum temperature of Thailand using mapping analysis method: A case study of summer 1987 to 2019." E3S Web of Conferences 158 (2020): 01001. http://dx.doi.org/10.1051/e3sconf/202015801001.
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This study aims to study distribution of air temperature characteristics and to analyse the trend of mean monthly maximum temperature changed in summer of Thailand from 1987 to 2019. The study was performed by gathering the temperature data from 83 meteorological stations around Thailand. The study focused on the months February to May in the years 1987 to 2019. Then, distribution of air temperature characteristics maps and graph of each month in each year are created to analyse the distribution and trend of mean monthly maximum temperature over the past 33 years. The results showed that, for every year, the mean monthly maximum temperature increased from February to April and decreased in May. Moreover, the maps presented that the air temperature in the western of Thailand was higher than the eastern of Thailand. Furthermore, the temperature trend illustrated that the mean monthly maximum temperature of all months in summer was increasing, especially May. Totally, the trend of the air temperature in summer was rising by 0.0087°C per year.
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Allard, Jason, Paul C. Vincent, Jeromy R. McElwaney, and Gerrit Hoogenboom. "A Comparison of Temperature Data from Automated and Manual Observing Networks in Georgia and Impacts of Siting Characteristics." Journal of Atmospheric and Oceanic Technology 33, no. 7 (2016): 1473–94. http://dx.doi.org/10.1175/jtech-d-15-0161.1.
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AbstractThe objectives of this study were to compare average monthly and seasonal maximum and minimum temperatures of the Georgia Automated Environmental Monitoring Network (AEMN) to those of geographically close (i.e., paired) manual observations from U.S. Historical Climatology Network (USHCN) stations and Cooperative Observer Program (COOP) stations for the period 2002–13, and to evaluate the extent to which differences in siting characteristics of paired AEMN–USHCN stations contribute to the temperature differences. Correlations for monthly and seasonal maximum and minimum temperatures of paired AEMN–USHCN and AEMN–COOP stations were high and almost always significant, although the correlations for seasonal minimum temperatures were slightly lower than those of maximum temperatures, especially for summer. Monthly maximum and minimum temperatures and seasonal maximum temperatures of paired AEMN–USHCN and AEMN–COOP stations were significantly different in only a few instances, while seasonal minimum temperatures were more often significantly different, particularly for summer. The stronger relationship between maximum temperatures than minimum temperatures for paired stations is logical given that minimum temperatures typically occur when a shallow, decoupled nocturnal boundary layer is more sensitive to local conditions [e.g., land use/land cover (LULC)]. Stepwise regressions confirmed that a portion of the variance of seasonal minimum temperatures of paired AEMN–USHCN stations was explained by differences in LULC, while the variance in seasonal maximum temperatures was explained better by differences in elevation. Despite the generally close relationships between temperatures of paired stations and a portion of the differences being explained, an abrupt change from manual networks to the AEMN without data adjustments would change the Georgia climate record on monthly and seasonal time scales.
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SINGH, VIVEKANAND, and ANSHUMAN SINGH. "Variation of temperature and rainfall at Patna." MAUSAM 68, no. 1 (2021): 161–68. http://dx.doi.org/10.54302/mausam.v68i1.445.
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In this paper, the variation of temperature and rainfall at Patna are analysed using simple non-parametric tests. The trends in the annual maximum and minimum daily temperatures, annual rainfall, annual maximum daily rainfall, number of rainy days in a year, the annual average rainfall per rainy day and the ratio of maximum to average rainfall per rainy day at Patna have been examined. Tends in total monthly rainfall, Highest daily rainfall in a month and number of rainy days in a month have also been determined for every month in a year. The monthly trends of data using simple Mann-Kendall test indicated statistically significant changes in rainfall pattern for the city.
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Zubaidi, Salah L., Hussein Al-Bugharbee, Khalid Hashim, et al. "Prediction and Forecasting of Maximum Weather Temperature Using a Linear Autoregressive Model." IOP Conference Series: Earth and Environmental Science 877, no. 1 (2021): 012031. http://dx.doi.org/10.1088/1755-1315/877/1/012031.
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Abstract This paper investigates the autoregressive (AR) model performance in prediction and forecasting the monthly maximum temperature. The temperature recordings are collected over 12 years (i.e., 144 monthly readings). All the data are stationaries, which is converted to be stationary, via obtaining the normal logarithm values. The recordings are then divided into 70% training and 30% testing sample. The training sample is used for determining the structure of the AR model while the testing sample is used for validating the obtained model in forecasting performance. A wide range of model order is selected and the most suitable order is selected in terms of the highest modelling accuracy. The study shows that the monthly maximum temperature can accurately be predicted and forecasted using the AR model.
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Janik, Gergely, Zoltán Pödör, András Koltay, et al. "Effects of Meteorological and Site Parameters on the Health Status of Beech (Fagus sylvatica L.) Forests in Hungary." Acta Silvatica et Lignaria Hungarica 16, no. 2 (2020): 67–78. http://dx.doi.org/10.37045/aslh-2020-0005.
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The influence of meteorological parameters on the health status of beech (Fagus sylvatica L.) was analyzed using long term datasets (1989-2010) collected in 15 sample plots located in Hungary’s main beech regions. Leaf loss values were correlated with different meteorological parameters as explanatory variables. Analysis was performed by the CReMIT (Cyclic Reverse Moving Intervals Techniques) method. Weather, stand, and site parameters were also examined with PCA for comparison. Leaf loss levels showed stronger correlations with maximum monthly temperatures than with monthly precipitation sums. The monthly number of summer days and monthly number of hot days displayed a similar correlation to leaf loss as the maximum monthly temperature did. The correlations were regularly stronger and more frequent on more arid sites where the climate is less favorable for beech. Temperature affected leaf loss more than precipitation did. Our results show that beech forests may suffer heavy damage if climate change continues as projected.
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Rahman, Mizanur, Hasan Imam, Sabuj Roy, Farhana Hoque, Urmee Ahsan, and Abubakar Abdullah. "Recent Trends of Mean Maximum and Minimum Air Temperatures in Bangladesh." Nepal Journal of Science and Technology 21, no. 2 (2022): 57–72. http://dx.doi.org/10.3126/njst.v21i2.62356.
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The annual, seasonal, and monthly maximum and minimum air temperature time series for 34 stations in Bangladesh have been examined during the period 1981– 2020 in this study. Three statistical tests were used in the analysis namely Mann–Kendall, Sen’s slope estimator, and linear regression, respectively. 47% of stations experienced significantly rising maximum air temperature trends during the pre-monsoon, 100% during the monsoon, 74% during the post-monsoon, and 24% during the winter season, respectively. Similar findings have been made about minimum air temperatures during the pre-monsoon, monsoon, post-monsoon, and winter seasons in 41, 91, 41, and 35% of stations over Bangladesh. According to the linear regression technique, the significant increasing trends of the maximum air temperatures at Patuakhali and Mongla stations are 0.83°C/decade and 0.82°C/decade in February and October, respectively. Furthermore, at Sandwip and M. Court, the significant increasing minimum air temperature trends in July and March are 0.26°C/decade and 0.66°C/decade, respectively. The highest monthly maximum and minimum air temperature time series value falls (decreases) were seen in January over the stations at Mongla (-0.58°C/decade) and Sandwip (-0.63°C/decade), respectively. This information will be useful in developing adaptation plans to mitigate the harmful effects of climate change. Vulnerability assessments, disaster management, enhanced structure design, institutional reform, and antiextreme climate engineering are some of the viable climate change adaptation approaches in Bangladesh due to rising temperatures.
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Medeiros, Raimundo Mainar de, Luciano Marcelo Fallé Saboya, Manoel Vieira de Fança, Romildo Morant de Holanda, Moacyr Cunha Filho, and Wagner Rodolfo de Araújo. "Monthly, annual and decadal variability of extreme and mean air temperatures in Parnaguá – Pi, Brazil." Research, Society and Development 11, no. 7 (2022): e35811730082. http://dx.doi.org/10.33448/rsd-v11i7.30082.
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Aiming at the delimitation of the buoyancy of the maximum temperature (TX), minimum temperature (Tn) and average temperature (Tm) of the air in the municipal area of Parnaguá and the lagoon of that municipality. With the development and agricultural expansion, large areas are being deforested, not taking into account the contribution of meteorological factors among them, especially temperatures, can minimize the occurrence of damage from anomalous effects that may happen. TX, Tn and Tm data estimated by the estima software were used - T between the years 1960 - 2019, monthly, annual, maximum and minimum values were obtained. Observing the variability of TX, Tn and Tm, the hottest quarter and its monthly and annual values were delimited, as well as the observed absolute maximum and minimum values. The results show that in the hot period the possibilities of fires and fires increase and in green areas it is beneficial to the production of pastures and grain. Such delimitations of the hottest quarters and the information on the times of lowest maximum air temperature served as a warning to federal, state, municipal authorities and decision makers to carry out better planning. The average temperature is the representation of the variability and its oscillations of extreme temperatures, any variability in these elements the average temperatures adapt to their oscillations and result from the synoptic systems active in the rainy and dry season as well as from the impacts on the environment and its elevation in relation to sea level.
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Zamfirova, M. S., and V. M. Khokhlov. "Air temperature and precipitation regime in Ukraine in 2021-2050 by CORDEX model ensemble." Ukrainian hydrometeorological journal, no. 25 (July 16, 2020): 17–27. http://dx.doi.org/10.31481/uhmj.25.2020.02.
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Global temperatures over the period of 2081–2100 are expected to rise by 0.3–4.8 °C compared to the period of 1986–2005. According to the previous studies, the average annual air temperature in all regions of Ukraine will keep increasing in the near future and the maximum increase in precipitation is expected mainly in the western and northern regions during winter and spring, whereas the decrease in precipitation will be registered in the central, eastern and southern regions during summer and autumn. This article aims to identify the features of changes in air temperature and precipitation for different regions of Ukraine in 2021–2050 based on the modelling results of the ensemble of CORDEX models as per the RCP4.5 scenario. 16 simulation runs for 7 regional climate models were selected for the analysis and the results were presented for five regional centers of Ukraine: Kyiv, Lviv, Kropyvnytskyi, Kharkiv and Odesa.
 It is shown that future monthly precipitation in all regions tends to increase by an average of 20–40 mm during autumn, winter and spring, whereas the decrease is expected to occur in summer. According to some models, the monthly precipitation will be close to zero in the Southern Ukraine in July and August, which is typical for the Mediterranean climate. Compared to the period of 1961–1990, the average monthly temperature will undergo small changes (up to 1 °C) in spring and autumn, while the temperature in summer and winter will increase by 2.5–3.5 °C. In Odesa, in contrast to the present-day situation, a positive average monthly air temperature will be expected to be recorded throughout the whole year, and only 25% of the runs show negative average monthly minimum temperatures. In the Northern Ukraine, the average monthly minimum and maximum temperatures in winter will increase by 2.0–2.5 °C, and in summer only the maximum air temperature will increase significantly.
 Thus, we can assume a change in the regime of moisture supply in Ukraine over the next thirty years. One can also assume a high probability of snow cover absence throughout the whole winter in the Southern Ukraine as a result of positive temperatures.
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Yildirim, Altan, Hakan Erdem, Selim Kilic, Sertac Yetiser, and Alaaddin Pahsa. "Effect of Climate on the Bacteriology of Chronic Suppurative Otitis Media." Annals of Otology, Rhinology & Laryngology 114, no. 8 (2005): 652–55. http://dx.doi.org/10.1177/000348940511400812.
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Objectives: We evaluated the correlation between the microbial content of chronic suppurative otitis media (CSOM) and regional climatic parameters. Methods: We assessed the interrelations between monthly mean records of temperature, maximum temperature, atmospheric pressure, and humidity and the aerobic microbial flora in CSOM. Results: Forty-three bacteria of Enterobacteriaceae, 67 staphylococcal spp, 51 Pseudomonas aeruginosa, 9 Streptococcus pneumoniae, 1 α-hemolytic Streptococcus, 1 Enterococcus sp, and 2 Edwardsiella tarda strains were recovered from 173 patients with CSOM. There was a good relationship between enteric bacteria and monthly mean temperature (r = 0.501) and significant colonization rates due to increasing monthly mean temperature (p = .040) and monthly mean maximum temperature values (p = .048). Conclusions: When the weather warmed, the frequency of isolation of enteric bacteria increased significantly. Temperature changes may affect the enteric bacterial colonization of CSOM.
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Arguez, Anthony, and Scott Applequist. "A Harmonic Approach for Calculating Daily Temperature Normals Constrained by Homogenized Monthly Temperature Normals." Journal of Atmospheric and Oceanic Technology 30, no. 7 (2013): 1259–65. http://dx.doi.org/10.1175/jtech-d-12-00195.1.
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Abstract NOAA released the new 1981–2010 climate normals in July 2011. These included monthly and daily normals of minimum and maximum temperature. Monthly normals were computed from monthly temperature values that were corrected for biases (i.e., homogenized) due to changes in observing practices over the course of the normals period (station moves, changes in observation time, and changes in instrumentation). Daily temperature observations, however, are not homogenized, which could lead to inconsistencies between the daily and monthly normals. This study offers a constrained harmonic technique that forces the daily temperature normals to be consistent with the monthly temperature normals. This approach replaces the cubic spline interpolation of monthly temperature normals that was used to compute earlier versions of NOAA's daily temperature normals. It effectively passes the homogenization applied at the monthly scale down to the daily scale, resulting in a smooth annual cycle devoid of day-to-day sampling variability and intermonth discontinuities.
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CICHI, DANIELA DOLORIS, MIHAI CICHI, and NICOLAE GHEORGHIU. "THERMAL REGIME DURING COLD ACCLIMATION AND DORMANT SEASON OF GRAPEVINES IN CONTEXT OF CLIMATE CHANGES- HILLS OF CRAIOVA VINEYARD (ROMANIA)." "Annals of the University of Craiova - Agriculture, Montanology,Cadastre Series " 51, no. 1 (2020): 50–59. http://dx.doi.org/10.52846/aamc.2021.01.07.
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The thermal regime during the autumn-winter seasons plays a decisive role in cold acclimation and survival grapevine in cold climates. This study aims at assessing the time variability of the thermal regime during dormant season, between 1961-2021, in the Hills of Craiova vineyard and its potential implications on the grapevine, especially regarding its acclimation to cold and its vulnerability to frost. The following observations and analytical data were used in order to assess parameters and indicators with negative thermal stress potential: minimum and maximum temperature (daily, monthly averages), absolute maximum and minimum monthly temperatures, the duration of frost (days), the frequency of several low-temperature thresholds and the temperatures preceding frost episodes.
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Wankhede, Sachin Yadavrao, Ramkrushna Gandhiji Idapuganti, Ulhas Vyankatrao Galkate, and Yenumula Gerard Prasad. "Decadal Trend Analysis of Maximum Temperature at Nagpur District of Maharashtra, India." Journal of Scientific Research and Reports 31, no. 4 (2025): 360–78. https://doi.org/10.9734/jsrr/2025/v31i42957.
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An attempt was made for decadal trend analysis of maximum temperature for monthly, seasonal and annual time series over a period of 1985 to 2024 using the Mann-Kendall Test and Sen’s Slope Estimator method at Nagpur district of Maharashtra. The annual trend in maximum temperatures from 1985 to 2024 showed non-significant increase of 0.004°C. Significant increase of maximum temperature was observed during Northeast monsoon season at 90% confidence level, with a rise of 0.025°C. Winter and summer temperatures exhibit minor, non-significant decreases. Among the months, November showed significant increase of 0.024°C. Between 1985 and 1994, the annual maximum temperatures showed no significant trend. The SW Monsoon experienced non-significant decrease of 0.025°C, while the NE Monsoon season showed a non-significant increase of 0.033°C. Winter recorded increase of 0.088°C, while summer showed no trend. January noticed non-significant increase of 0.238°C. From 1995 to 2004, a statistically significant annual increase of 0.100°C was observed. The NE Monsoon and summer seasons experienced significant increasing trends, with increases of 0.220°C and 0.214°C, respectively. The SW Monsoon season, however, showed a non-significant decreasing trend of 0.150°C. April experienced a significant rise in maximum temperatures of 0.267°C, while August showed a significant decrease of 0.167°C. During 2005–2014, the annual trend showed non-significant decrease of 0.013°C. The NE Monsoon season and winter exhibited decreasing trends, with winter showing a significant decline of 0.100°C at the 90% confidence level. Monthly non-significant decreasing trends was observed during January (-0.125°C) and February (-0.133°C). For the recent decades 2015–2024, annual maximum temperatures observed, non-significant decline of 0.020°C. The SW Monsoon season exhibited, non-significant increase of 0.020°C, while the NE Monsoon and winter seasons experienced non-significant decreases. Summer showed, non-significant decreasing trend, with decline of 0.230°C. Among monthly trends, April (-0.320°C) and May (-0.230°C) exhibited the most notable non-significant decreases.
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M., Cüneyt Bağdatlı Eda Nur Arıkan. "Evaluation of Monthly Maximum, Minimum and Average Temperature Changes Observed for Many Years in Nevsehir Province of Turkey." World Research Journal of Agricultural Sciences 7, no. 2 (2020): 209–20. https://doi.org/10.5281/zenodo.3833182.
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Evaluation of Monthly Maximum, Minimum and Average Temperature Changes Observed for Many Years in Nevsehir Province of Turkey In this research, minimum, maximum and average temperature values between 1970 and 2019 in Center of Nevşehir Province, Ürgüp and Avanos districts in Turkey were examined. Sperman Rho and Mann Kendall statistical correlation tests were used in the analysis phase. As a result, the trends of temperature changes in years are revealed. According to trend analysis results, the average minimum temperature for long years in Avanos district is calculated as -1.20 °C. Maximum temperature is 26,6 °C and the average of all temperature values is 12.18 °C. The average minimum temperature for many years in center of Nevsehir province is calculated as 1.99 0C, the maximum temperature is 24 0C and the average of all temperature values is calculated as 10.73 0C. In Ürgüp district, the minimum temperature for long years was calculated as -4.20 0C, the maximum temperature is 18.48 0C, and the average of all temperature values are 10.32 0C. As a results; It has been observed that there were increasing trend in years of spring, winter, autumn and summer in Nevsehir province and No trend was observed in Avanos and Ürgüp districts at maximum temperature values. While increasing trend is observed in Avanos district and Nevşehir Province in minimum temperature parameters, no change was observed in Ürgüp district. Increasing changes were observed in the average temperatures in all districts. Key words: Temperature, Global Climate Change, Trend Analysis, Nevsehir Province, Turkey
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Stott, T., and S. Marks. "Effects of plantation forest clearfelling on stream temperatures in the Plynlimon experimental catchments, mid-Wales." Hydrology and Earth System Sciences 4, no. 1 (2000): 95–104. http://dx.doi.org/10.5194/hess-4-95-2000.
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Abstract. Hourly stream temperatures monitored over 28 months, which spanned a 3 month period of environmentally sensitive plot-scale harvesting of 20 ha. (20%) of the Nant Tanllwyth catchment (0.89 km2) on the south side of the main stream in early 1996, resulted in a 0.58°C (p< 0.001) increase in monthly mean stream temperature. Over the same 28 month experimental period, there was no significant increase in the monthly mean air temperature recorded at a nearby automatic weather station. Monthly mean temperatures are highest in July and August in the year before and the year after the clearfelling, and one of the main effects of the clearfelling was to decrease the difference between the monthly mean stream and air temperatures. Despite the air temperatures being cooler in the post-clearfelling year, the stream temperatures still showed an increase in the summer months. Monthly mean maximum stream temperatures, also highest in July and August in the year before and the year after the clearfelling, showed a marked increase of 7.0°C: in July and 5.3°C in August from the pre- to the post-clearfelling years, while monthly mean minimum air temperatures actually showed a slight decrease for the same months. The likely effects on stream fauna are discussed, as are suggestions for, and likely effects of, buffer strips alongside the streams. Keywords: stream temperature; air temperature; ground surface temperature; clearfelling; Plynlimon
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Timmer, Reed P., and Peter J. Lamb. "Relations between Temperature and Residential Natural Gas Consumption in the Central and Eastern United States." Journal of Applied Meteorology and Climatology 46, no. 11 (2007): 1993–2013. http://dx.doi.org/10.1175/2007jamc1552.1.
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Abstract The increased U.S. natural gas price volatility since the mid-to-late-1980s deregulation generally is attributed to the deregulated market being more sensitive to temperature-related residential demand. This study therefore quantifies relations between winter (November–February; December–February) temperature and residential gas consumption for the United States east of the Rocky Mountains for 1989–2000, by region and on monthly and seasonal time scales. State-level monthly gas consumption data are aggregated for nine multistate subregions of three Petroleum Administration for Defense Districts of the U.S. Department of Energy. Two temperature indices [days below percentile (DBP) and heating degree-days (HDD)] are developed using the Richman–Lamb fine-resolution (∼1° latitude–longitude) set of daily maximum and minimum temperatures for 1949–2000. Temperature parameters/values that maximize DBP/HDD correlations with gas consumption are identified. Maximum DBP and HDD correlations with gas consumption consistently are largest in the Great Lakes–Ohio Valley region on both monthly (from +0.89 to +0.91) and seasonal (from +0.93 to +0.97) time scales, for which they are based on daily maximum temperature. Such correlations are markedly lower on both time scales (from +0.62 to +0.80) in New England, where gas is less important than heating oil, and on the monthly scale (from +0.55 to +0.75) across the South because of low January correlations. For the South, maximum correlations are for daily DBP and HDD indices based on mean or minimum temperature. The percentiles having the highest DBP index correlations with gas consumption are slightly higher for northern regions than across the South. This is because lower (higher) relative (absolute) temperature thresholds are reached in warmer regions before home heating occurs. However, these optimum percentiles for all regions are bordered broadly by surrounding percentiles for which the correlations are almost as high as the maximum. This consistency establishes the robustness of the temperature–gas consumption relations obtained. The reference temperatures giving the highest HDD correlations with gas consumption are lower for the colder northern regions than farther south where the temperature range is truncated. However, all HDD reference temperatures greater than +10°C (+15°C) yield similar such correlations for northern (southern) regions, further confirming the robustness of the findings. This robustness, coupled with the very high correlation magnitudes obtained, suggests that potentially strong gas consumption predictability would follow from accurate seasonal temperature forecasts.
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Matev, Simeon, Petko Bojkov, Dimitar Krenchev, and Nina Nikolova. "Temperature gradient along the northern slope of the Western Rhodopes." Review of the Bulgarian Geological Society 84, no. 3 (2023): 249–52. http://dx.doi.org/10.52215/rev.bgs.2023.84.3.249.
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The article examines the values of the vertical temperature gradient along the northern slope of the Western Rhodopes Мountain. The average monthly temperatures in three stations located between 290 and 1535 m a.s.l. were used as the basis of the calculations. Calculations were made for the following temperature indicators: monthly average, average minimum and average maximum, and absolute minimum and absolute maximum. The study covers the period July 2022 – August 2023. The values of the vertical temperature gradient are greatest in the summer and smallest in the autumn-winter period. In the lower part of the studied territory, in winter the gradient also has negative values, due to temperature inversions, and in summer its values are three times greater than in the upper part, due to the greater turbulence of the atmosphere.
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Kundzewicz, Zbigniew W., and Damian Józefczyk. "Temperature-related climate extremes in the Potsdam observation record." Geografie 113, no. 4 (2008): 372–82. http://dx.doi.org/10.37040/geografie2008113040372.
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This paper examines temperature-related climate extremes in the unique long-term gapfree record at the Secular Meteorological Station in Potsdam. Increasing tendencies in daily minimum temperature in winter and daily maximum temperature in summer, as well as monthly means of daily minimum temperatures in winter months and of daily maximum temperatures in summer months are illustrated. Also the numbers of hot days and of summer days (with maximum daily temperature exceeding 30 °C and 25 °C, respectively) have been increasing. In agreement with warming of winter minimum temperatures, the numbers of frost days (with minimum daily temperature below 0 °C) and of ice days (with maximum daily temperature below 0 °C) have been decreasing. However, low correlation coefficient and huge scatter illustrate strong natural variability, so that the occurrence of extremes departs from the general underlying tendency.
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Ranjeet, S. K. Sharma, Susma Jain, and H. L. Khapediya. "Statistical Model for Annual Trends and Magnitude of Climatic Variability across Locations from the Malwa Plateau Agroclimatic Zone of Madhya Pradesh, India." International Journal of Environment and Climate Change 13, no. 9 (2023): 3073–87. http://dx.doi.org/10.9734/ijecc/2023/v13i92743.
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Global climate change has affected the local weather patterns in different regions, especially in India. To manage the water resources effectively, it is important to quantify the local changes in the climatic variables. One of the key variables is precipitation, which is often used as an indicator of climate change. This study aims to examine the temporal variability of rainfall in the Malwa Agroclimatic Zone from 1991 to 2020 (30 years) and to assess its impact on the hydrological status of the districts in this zone. The Mann-Kendall and Sen's tests are used to detect the trend and magnitude of change in the annual precipitation time series. The autocorrelation effects are removed before applying the Mann-Kendall test. The results show that on an annual basis, Indore (Z 1.21 & Q 7.86), Mandsaur (Z 0.82 & Q 3.697), Neemuch (Z 1.03 & Q 3.488), Rajgarh (Z 0.93 & Q 0.5658), Ratalm (Z 0.64 & Q 3.525), Shajapur (Z = 0.57 & Q 3.164) and Ujjain (Z 0.11 & Q 0.692) have an increasing but not statistically significant trend in rainfall, while Dewas (Z -0.07 and Q -0.189) has a decreasing but not statistically significant trend in rainfall. The annual and monthly maximum temperature decreased in the Indore district, while the minimum temperature showed an increasing and decreasing trend. Dewas district also had a decreasing maximum temperature and an increasing minimum temperature. Ujjain district had a decreasing trend for maximum temperature and a significant annual increasing trend for minimum temperature. Shajapur district had a significant annual decreasing trend for maximum temperature and a significant annual and monthly (January and September) increasing trend for minimum temperature. Neemuch district had a significant annual increasing trend for both maximum and minimum temperature, as well as a significant monthly (January) increasing trend for minimum temperature. Ratlam district had a significant annual and monthly (January and September) increasing trend for minimum temperature. Mandsaur and Rajgarh districts had non-significant increasing trends for both maximum and minimum temperature, except for significant monthly (January and September) increasing trends.
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Zheng, Yonghong, and Rob Wilson. "Tree Ring Blue Intensity-Based August Temperature Reconstruction for Subtropical Central China." Forests 15, no. 8 (2024): 1428. http://dx.doi.org/10.3390/f15081428.
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Tree-ring blue intensity (BI) has the potential to provide information on past summer temperatures of a similar quality to that of tree-ring maximum latewood density and at a substantially reduced cost. To explore the applicability of BI in subtropical regions, the inverted BI for the earlywood, latewood, and the delta BI (DBI) parameters, together with tree-ring width of subalpine fir (Abies fargesii Franch.) in the Shennongjia area of China, were measured, and the corresponding chronologies were developed. The relationships between these chronologies and monthly precipitation, monthly mean minimum temperature, monthly mean temperature, and monthly mean maximum temperature were explored through correlation analysis. Results show that the DBI chronology is closely related to the temperature in August of the current year, indicating that BI, specifically delta BI, data are suitable for use in dendroclimatology studies in subtropical areas. The resultant mean temperature reconstruction for August, based on DBI, explains 40.8% of the temperature variance and is robustly validated using independent periods from the calibration. This pilot study not only highlights the potential of DBI for temperature reconstruction in China but also offers valuable insights into historical climate variations in the Shennongjia region. Moreover, it shows the potential for utilizing such tree-ring data from low-latitude regions to derive past climate data in subtropical warm-humid zones.
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van Wijngaarden, W. A., and A. Mouraviev. "Seasonal and Annual Trends in Australian Minimum/Maximum Daily Temperatures." Open Atmospheric Science Journal 10, no. 1 (2016): 39–55. http://dx.doi.org/10.2174/1874282301610010039.
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Seasonal and annual trends in Australian minimum and maximum temperatures were studied. Records of daily minimum and maximum temperatures averaged over each month, extending as far back as 1856 were examined. Over 1/2 million monthly temperature values were retrieved from the Australian Bureau of Meteorology for 299 stations. Each station had an average of 89 years of observations. Significant step discontinuities affected the maximum temperature data in the 19th century when Stevenson screens were installed. The temperature trends were found after such spurious data were removed and averaged over all stations. The resulting trend in the minimum (maximum) daily temperature was 0.67 ± 0.19 (0.58 ± 0.26) oC per century for the period 1907-2014. Decadal fluctuations were evident in the maximum daily temperature with most of the increase occurring in the late 20th century. The minimum and maximum daily temperature trends were also found for the various seasons. The minimum daily temperature trend exceeded the maximum daily temperature trend for all seasons except during June to August. The largest increases in minimum temperature as well as the smallest maximum temperature increases were found for the region north of 30 oS latitude and east of 140 oE longitude. There was also evidence that urban stations had greater increases in maximum daily temperature than those located in a rural environment.
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Yildirim, A., H. Erdem, S. Kilic, S. Yetiser, and A. Pahsa. "<p>Effect of climate on the bacteriology of chronic suppurative otitis media</p>." Community Ear and Hearing Health 4, no. 6 (2007): 7. http://dx.doi.org/10.56920/cehh.157.
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Objectives: We evaluated the correlation between the microbial content of chronic suppurative otitis media (CSOM) and regional climatic parameters.
 Methods: We assessed the interrelations between monthly mean records of temperature, maximum temperature, atmospheric pressure, and humidity and the aerobic microbial flora in CSOM.
 Results: Forty-three bacteria of Enterobacteriaccae, 67 Staphylococcal spp, 51 Pseudomonas aeruginosa, 9 Streptococcus pneumoniae, 1 alpha-hemolytic Streptococcus, 1 Enterococcus sp, and 2 Edwardsiella tarda strains were recovered from 173 patients with CSOM. There was a good relationship between enteric bacteria and monthly mean temperature (r = 0.501) and significant colonization rates due to increasing monthly mean temperature (p = .040) and monthly mean maximum temperature values (p = .048).
 Conclusions: When the weather warmed, the frequency of isolation of enteric bacteria increased significantly. Temperature changes may affect the enteric bacterial colonization of CSOM.
 Published courtesy of:Ann Otol Rhinol Laryngol. 2005; 114(8): 652-655
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Parajuli, Prem B., and Avay Risal. "Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale." Climate 9, no. 11 (2021): 165. http://dx.doi.org/10.3390/cli9110165.
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This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.
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KESETYANINGSIH, Tri Wulandari, Sri ANDARINI, Sudarto SUDARTO, and Henny PRAMOEDYO. "The Minimum-Maximum Weather Temperature Difference Effect on Dengue Incidence in Sleman Regency of Yogyakarta, Indonesia." Walailak Journal of Science and Technology (WJST) 15, no. 5 (2018): 387–96. http://dx.doi.org/10.48048/wjst.2018.2277.
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Dengue is a viral disease, transmitted by Aedes aegypti, and is still a big problem in tropical areas, including Indonesia, where the temperatures are relatively warm and suitable for vector mosquito life. In the dry season, the day and night temperature differences are quite sharp and, at that time, the number of dengue cases is low. In this study, the difference between day and night temperature is referred to as daily temperature fluctuation and represented by the maximum and minimum temperature difference in each month. The research was conducted in Sleman Regency, Yogyakarta Province, Indonesia, as an endemic area, and the data were collected from 4 endemic areas in Sleman; Gamping, Godean, Sleman, and Depok districts. The data collected were quantitative with serial data retrospective. Secondary data of monthly dengue incidence in the years 2008 - 2013 were obtained from the Regency Health Office and used as a dependent variable. Monthly minimum and maximum temperatures in the same periods were obtained from the Agency of Meteorology, Climatology, and Geophysics. The differences between the minimum and maximum temperatures were calculated, to be used as independent variable data, and represented the different day and night temperatures of the month. Data were analyzed by using linear regressions to determine the influence of fluctuating temperature on the incidence of dengue. Results show that fluctuating temperature affected dengue incidence in the districts of Godean (p = 0.000; R2 = 0.207) and Gamping (p = 0.006; R2 = 0.125), but did not affect it in Sleman (p = 0.164) or Depok (p = 0.075). The data suggests that fluctuating temperature affected dengue incidence with powers of 20.7 % in Godean and 12.5 % in Gamping.
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Al-Ataby, Iqbal, and Amani Al-Tmimi. "Estimate the probability density function of maximum temperature for the Middle East." Przegląd Naukowy Inżynieria i Kształtowanie Środowiska 29, no. 4 (2020): 517–31. http://dx.doi.org/10.22630/pniks.2020.29.4.45.
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Pollution is one reasons for increase temperature which leads to increase the heat waves which have large socioeconomic and healthy impacts on Middle East. By using monthly daily mean of maximum temperature (C°) at height (2m) covered middle east as a grid of (1581) points for selected months (March, April, May) represent spring and (Jun, July, August) represent Summer for the period 1979 to2018, from the ECMWF, model ERA-interim. Many PDFs have been proposed in recent past, but in present study Logistic, Rayleigh and Gamma distribution are used to describe the characteristics of maximum temperature. This paper attempts to determine the best fitted probability distribution of maximum temperature. To check the accuracy of the predicted data using theoretical probability distributions the goodness of fit criteria Z-test used in this paper. According to the goodness-of-fit criteria and from the graphical comparisons it can be said that Logistic distribution provides the best fit for the observed monthly daily mean of maximum temperature data.
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Rust, Henning W., Tim Kruschke, Andreas Dobler, Madlen Fischer, and Uwe Ulbrich. "Discontinuous Daily Temperatures in the WATCH Forcing Datasets." Journal of Hydrometeorology 16, no. 1 (2015): 465–72. http://dx.doi.org/10.1175/jhm-d-14-0123.1.
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Abstract The Water and Global Change (WATCH) forcing datasets have been created to support the use of hydrological and land surface models for the assessment of the water cycle within climate change studies. They are based on 40-yr ECMWF Re-Analysis (ERA-40) or ECMWF interim reanalysis (ERA-Interim) with temperatures (among other variables) adjusted such that their monthly means match the monthly temperature dataset from the Climatic Research Unit. To this end, daily minimum, maximum, and mean temperatures within one calendar month have been subjected to a correction involving monthly means of the respective month. As these corrections can be largely different for adjacent months, this procedure potentially leads to implausible differences in daily temperatures across the boundaries of calendar months. We analyze day-to-day temperature fluctuations within and across months and find that across-months differences are significantly larger, mostly in the tropics and frigid zones. Average across-months differences in daily mean temperature are typically between 10% and 40% larger than their corresponding within-months average temperature differences. However, regions with differences up to 200% can be found in tropical Africa. Particularly in regions where snowmelt is a relevant player for hydrology, a few degrees Celsius difference can be decisive for triggering this process. Daily maximum and minimum temperatures are affected in the same regions, but in a less severe way.
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JASWAL, A. K. "Recent winter warming over India – spatial and temporal characteristics of monthly maximum and minimum temperature trends for January to March." MAUSAM 61, no. 2 (2021): 163–74. http://dx.doi.org/10.54302/mausam.v61i2.798.
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In the backdrop of recent warmer winters over India, temperature series of 174 stations well distributed over the country were statistically analyzed to document the long term variations and trends in monthly mean maximum and minimum temperatures for January to March. From the trend analysis, February month has emerged as the warmer winter month over North India where increase in both maximum (+0.29° C / decade) and minimum (+0.38° C / decade) temperatures is highest with noteworthy increase in maximum temperature at a rate 1.5 times that of the South India averaged increase. Spatially, North India minimum temperature trends for February and March and South India maximum temperature trends for all months are more coherent.
 
 Both day-time and night-time total cloud amounts are increasing significantly over Indo-Gangetic plains and south peninsula and decreasing significantly in central and east India. However increase in temperatures over extreme south peninsula in January and March is difficult to explain on the basis of increase in day-time total cloud amount indicating strong influence of other climatic factors. At the same time, sea surface temperatures of the Arabian Sea and the Bay of Bengal are rising and there is strong positive correlation between land surface temperatures and sea surface temperatures suggesting significant contribution of warmer sea waters which may have important climatic implications over neighbouring regions.
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SINHA, L., A. K. CHOWDHARY, and H. K. DWIVEDI. "ANALYSIS OF TREND IN MONTHLY AND ANNUAL MAXIMUM TEMPERATURE OVER HOMOGENEOUS TEMPERATURE REGIONS OF INDIA." i-manager’s Journal on Civil Engineering 8, no. 4 (2018): 7. http://dx.doi.org/10.26634/jce.8.4.14449.
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Suci, An Nisa Nurul, Neviaty Putri Zamani, and Dietriech Geoffrey Bengen. "MAXIMUM THERMAL TOLERANCE OF TROPICAL MARINE GASTROPODS, Haliotis squamata (Reeve 1846)." Jurnal Ilmu dan Teknologi Kelautan Tropis 11, no. 3 (2019): 595–600. http://dx.doi.org/10.29244/jitkt.v11i3.25860.
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Data about maximum thermal tolerance in marine organisms are needed to prevent the extinction of species due to global warming. The aim of this study is determining the maximum lethal temperature of Haliotis squamata. In this study, H. squamata were placed in individual containers and exposed to 5 different levels of temperature (27°C, 28.5°C, 30°C, 31.5°C, and 33°C, n = 20). The temperature was raised 0.5°C per 12 hours starting from ambient conditions until target temperatures were reached. The mortality was monitored since animals moved to the individual containers. The results showed that the maximum thermal limit of H. squamata is 31.5°C and 33°C is the lethal temperature, the temperature level with the lowest survival rate (0.15). The IPCC predict that sea surface temperature will raise up to 4°C and monthly average sea surface temperature in Indonesia is around 26 – 31°C. That means in the next century average sea surface temperature could be more than the maximum thermal limit of H. squamata. Thus, early conservation is needed to protect H. squamata.
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Kean, J. M. "How accurate are methods for predicting phenology in New Zealand." New Zealand Plant Protection 66 (January 8, 2013): 124–31. http://dx.doi.org/10.30843/nzpp.2013.66.5560.
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Thermal accumulation (degree day) methods are routinely used to predict plant and insect phenology Depending on the data available prediction may involve three separate steps with associated errors estimating daily heat units from maximum and minimum temperatures; interpolating daily maxima and minima from monthly averages; and predicting future monthly averages from past climate potentially including climate change This research investigated the potential error in thermal accumulation totals arising from each of these factors at nine New Zealand sites Ten simple heat unit calculations were tested including two littleknown and three new methods Those utilising the true daily mean temperature performed best followed by 4step triangle and sine approximations Interpolating between monthly mean temperature extremes introduced much error into daily estimates and the use of predicted rather than observed monthly normals further increased error Specific recommendations are made for thermal accumulation methods depending on what temperature data are available