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Long homogeneous meteorological data is important to study climate change. Evaluating the impact of data inhomogeneity on analyzing average temperature trends in Huai river basin is value for accurately understanding the response of agriculture, ecology and water resources to climate change. In this study, based on the homogeneous data and observation data of daily average air temperature from the National Meteorological Information Center, the trends of annual and seasonal air temperatures during 1961 to 2018 were calculated using simple linear regression at 172 meteorological stations over Huai river basin. Then the impacts of data inhomogeneity on analyzing mean air temperature trends during 1961 to 2018 were evaluated by using two terms Crop rhizosphere microorganisms is crucial for their growth, development and adaptability to stress. A field pot experiment was conducted using Yannong19(YN) with strong resistance to late spring coldness and which were inhomogeneity impacts and contribution rates. The results showed that the average air temperature series of 96 meteorological stations in Huai river basin were inhomogeneous, accounting for 55.8% of the 172 total stations. Before and after the homogenization, the regional annual average air temperature both increased significantly. But the increasing rate was underestimated due to the data heterogeneity, and the influence was -0.015°C•10y-1 with a contribution of -6.6%. For each station, 35 stations (20.3%) was positively affected and the warming rate was overestimated with an average contribution of 21.3%, while 61 stations (35.5%) were negatively affected and the warming rate was underestimated with an average contribution of -43.6%. The influences of inhomogeneity for four seasons showed little difference, which were -0.016°C•10y-1, -0.014°C•10y-1, -0.016°C•10y-1 and -0.015°C•10y-1, respectively. However, because of the slowest increasing rate, the absolute value of inhomogeneity contribution was largest in summer with a contribution of -40.0%. The contributions of spring, autumn and winter were -4.7%, -8.0% and -4.3%. Inhomogeneity mostly affected the temperature rising rate at each station in spring, autumn and winter, while led to a turning of temperature trend before and after homogenization at 20 stations (11.6%) in summer. [ABSTRACT FROM AUTHOR]

Data from national meteorological stations in 90 counties of Jiangxi province during 2012-2021 and 8 microclimate stations in rice fields during 2017-2021 were used to analyze the differences in temperature between rice fields and stations, and the statistical results based on H1 (NS)(daily max temperature of national stations ≥35 °C), H1 (RS)(daily max temperature of rice fields ≥35 °C), H2 (NS)(daily max temperature of national stations ≥37°C) and H2 (RS) (daily max temperature of rice fields ≥ 37 °C ) were compared. Furthermore, proposing high-temperature damage indicators more suitable for early rice in Jiangxi, which would promoting capabilities of high-temperature monitoring and defense. The results showed that: (1) compared with the national stations, the rice fields had a cooling effect, and the Tmax(daily maximum temperature), T(daily average temperature), and Tmin(daily minimum temperature) were 0.6 °C, 0.4 °C, and 0.3 °C lower than national stations. What's more, the cooling effect increased with the growth of early rice, which showed as heading-maturity period>transplanting-booting period>sowing-transplanting period. (2) The cooling effect was higher in sunny days than in cloudy and rainy days during the high temperature period, and T, Tmax and Tmin of early rice field were 0.7 °C, 0.8 °C and 0.6 °C lower than that of the national stations. On cloudy and rainy days, the decrease in temperature of rice fields was similar. (3) There were significant differences in daily and hourly air temperature between 6 rice fields and the corresponding national stations during H1 (NS) heat damage occurred, and the cooling intensity of the rice field was greater at night than in the daytime. The Tmax, T and Tmin of the 6 fields were generally about 1.2 °C lower, which was strongest in Jinxi filed with T, Tmax and Tmin was 1.5 °C, 1.1 °C and 2.6 °C lower. (4) H1 (NS) was the largest and H2 (RS) was the smallest in terms of the number of counties affected by heat damage, the average duration, the average yield reduction simulation value of affected counties and the simulation value of the whole in recent 10 years based on different heat damage index. There was no significant difference in the result of average duration, the simulated average yield reduction rate of affected counties, and the simulated yield reduction rate of the whole based on H2 (NS) and H1 (RS), while they were all different with the result based on H1 (NS) or H2 (RS). And the simulated value of the reduction rate of the whole calculated by H2 (NS) was closer to the actual value. Therefore, national stations Tmax ≥37°C was more suitable as an index of heat damage for early rice in Jiangxi. [ABSTRACT FROM AUTHOR]

The seasonal temperature forecasting models in greenhouse based on multiple regression (MR), BP artificial neural networks (BPANN), random forest (RF) and support vector machine (SVM) were constructed using meteorological observations inside and outside the Venlo-type glass greenhouses from 27th February 2021 to 4th March 2023 at Nanjing University of Information Science & Technology, and then to validate all the models. The results showed that the fitting accuracy of the seasonal forecasting models for daily average and minimum air temperatures in the greenhouse was significantly higher than that of the seasonal forecasting models for daily maximum air temperature; the fitting accuracy of each model for air temperature inside the greenhouse in spring, summer and autumn was higher than that for winter. For the seasonal forecasting models of daily average air temperature and minimum air temperature, the fitting accuracy of the spring, summer and autumn forecasting models constructed by the four algorithms was higher, but the simulation effect of the RF model was more stable, and the coefficient of determination (R²) of the simulated values and the actual observed values were above 0.94, and the root mean square error (RMSE) and absolute error (MAE) were within 1.5 °C. For the seasonal forecast models of daily maximum temperature, the fitting accuracy of RF model for spring, summer and autumn was higher than other models in general, and its R² value was above 0.75. The MR model had higher accuracy for winter indoor air temperature and was more suitable for predicting winter greenhouse air temperature. The study concluded that it is feasible to choose the RF model to forecast the air temperature inside the glass greenhouse in spring, summer and autumn and the MR model to forecast the air temperature inside the glass greenhouse in winter, and this study can provide an important reference for the seasonal forecast of air temperature in Venlo-type glass greenhouse. [ABSTRACT FROM AUTHOR]

T-FACE (temperature-free air carbon dioxide enrichment）experimental platform was adopted. Four field treatments of winter wheat were set: field conventional temperature and CO2 concentration (CK), field conventional temperature and increase CO2 concentration to 575μmol·L−1 (C), field increase temperature (i.e., 2℃ above atmospheric temperature) and field conventional CO2 concentration (T), and field increase temperature (i.e., 2℃ above atmospheric temperature) and increase CO2 concentration to 575μmol·L−1 (CT) . Soil samples were collected at different soil layers (plough layer 0−14cm, plough bottom 14−33cm, pond layer 33−59cm and glebe layer 59−80cm) at sowing stage, overwintering stage, tillering stage and maturity stage of winter wheat, respectively, to analyze the effects of increasing atmospheric CO2 concentration and temperature on N and P content and availability in the soil. The results were as follows: (1)under the condition that CO2 concentration increased in the overwintering stage of winter wheat, the nitrate nitrogen content in pond layer of soil showed a tendency to decrease by increasing temperature. In the overwintering stage of winter wheat, except for T treatment, the nitrate nitrogen content of CK, C and CT treatment was lower than that of tilling layer during sowing stage. In the overwintering stage of winter wheat, the nitrate nitrogen content increased most obviously in CK treatment. (2) Under the condition of increasing CO2 concentration and temperature, the content of ammonium nitrogen in the soil at tillering stage and overwintering stage of winter wheat was significantly lower than that under normal CO2 concentration and temperature treatment. There was no obvious upward or downward trend in different soil layers. The content of ammonium nitrogen was relatively stable during the whole growing stage of winter wheat. However, under CT, C and T treatments, the content of ammonium nitrogen increased significantly at maturity stage of winter wheat, and the increasing trend of nitrate nitrogen was more significant under increasing temperature (P<0.05). During the whole growth stage of winter wheat, the ammonium nitrogen showed a trend of increasing first and then decreasing under C treatment, while CK, CT and T treatments showed a trend of increasing, decreasing and increasing. (3) The content of available P in CK treatment was significantly higher than other treatments in the whole growth stage of winter wheat. There was a significant difference in available P content between CK treatment and CT and T treatments at sowing stage, overwintering stage and tillering stage of winter wheat (P<0.05). The results can provide some scientific basis for rational application of N and P fertilizer, reducing unnecessary nutrient loss and preventing non-point source pollution under the condition of CO2 concentration and temperature increase caused by climate change in the future. [ABSTRACT FROM AUTHOR]

In order to improve the pertinence of meteorological services for high-quality wheat, according to quality measurement data of 6 strong gluten and medium strong gluten wheat varieties, 287 wheat samples from 72 counties in Henan province during 2017-2019, as well as corresponding meteorological and wheat growth period observation data, analytical methods as Person correlation, LSD multi comparison and sensitive coefficient, et al., were used to confirm the key meteorological factors that influence the planting quality of strong gluten wheat in Henan province. The results indicated that, except the south of southern Henan and western Henan area, it was suitable to develop high-quality strong gluten wheat in most areas of Henan province. 6 quality indexes as hardness index, crude protein etc. were affected by the meteorological conditions after jointing to different degrees, among them, air temperature and sunshine hours at jointing-heading and mature-harvest stage had significant effect on most quality indices, air temperature and sunshine hours at flowering-grain filling stage mainly affected hardness index, sedimentation value and water absorption, and at mature-harvest stage, precipitation had negative effect on flour water absorption. Comparing the absolute value of sensitive coefficient SV(i), the sedimentation value was the most sensitive to the average maximum air temperature at jointing-heading stage, SV(i) reached to 0.7954. For different developmental stages, the key meteorological factors for planting quality reaching the standard of strong gluten wheat were as follows: average maximum air temperature, air relative humidity and sunshine hours at jointing-heading stage, air relative humidity at flowering-grain filling stage, and average air temperature at mature-harvest stage. The results explained that the most important meteorological factors effecting the planting quality of strong gluten wheat was air temperature. [ABSTRACT FROM AUTHOR]

Based on the daily national meteorological data in spring of 2023, relationships between meteorological factors and agricultural production in China were analyzed using statistical methods. The results showed that the national average air temperature in spring of 2023 was 11.3℃, which was 0.6℃ higher than the same period from 1991 to 2020, but with significant fluctuations. The national average precipitation was 127.2mm, which was 7.4% lower than the same period from 1991 to 2020 and the lowest since 2012. The spatial distribution of precipitation was uneven, with an overall distribution characteristic of more in the middle and less in the north and south of China. The national average sunshine duration was 634.6h, which was close to the same period from 1991 to 2020. The most summer-harvesting areas had sufficient light and heat during the yield formation stage, which was conducive for increasing the number of grains per ear and forming large ears. However, strong temperature drops and snowfall in mid-March and late-April caused varying degrees of freezing damage to winter wheat and rapeseed in Shaanxi, Shanxi, Henan and other regions. Wheat of Shaanxi and Henan experienced severe continuous rain in late-May, with the rainy period highly overlapping the wheat maturity period, resulting in moldy grains and sprouting of mature wheat. The soil moisture of spring sowing area in the northeast China was generally suitable, and the progress of spring sowing was relatively smooth. During the sowing and seedling raising period, there was no significant low temperature and low light weather in early rice regions, but there was a periodic low temperature in late-April and mid-May, which delayed the turning green and tillering process of early rice. Moderate to severe agricultural drought has occurred in southern of Sichuan and central and northern of Yunnan, affecting the sowing and emergence of maize, as well as the transplanting of one season rice and tobacco. [ABSTRACT FROM AUTHOR]

When the daily average water temperature exceeds 32℃, the hatching rate and feeding rate of some warm water fish decrease with the increase of temperature, grow slowly or stop growing, and are easy to induce diseases. In summer, the water temperature in the fish pond is not always in the high temperature period. In this paper, based on the water and air temperature data of Fushun Aquaculture Meteorological Service Test Base from 2017 to 2019, the variation characteristics of water temperature in each layer of fish pond in summer were analyzed, and the prediction models of average and maximum water temperature on the sunny days were established by stepwise regression analysis. Results showed that the daily max. water temperature in each layer in summer occurs from 18:00 to 19:00, which lagged behind the temperature by 1-3 hours. The period when the water temperature ≥32℃ was mainly concentrated from 16:00 to 22:00, and the hourly average water temperature of each layer in this period was 32.9-33.1℃, 32.6-32.7℃ and 32.1-32.3℃, respectively. The water temperature of each layer fluctuated and rose with the temperature in summer, especially from mid-June to early-July, while the maximum values of temperature and water temperature appeared in late-July. The average number of days with water temperature ≥32℃ in summer was 23 days, accounting for a quarter of the whole summer, mainly from late July to mid-August. During this period, the daily average water temperature of each layer was 28.5-34.4℃, 28.2-34.1℃ and 27.9-33.9℃, respectively. The back substitution test in 2017-2018 and the forecast test in 2019 showed that the average absolute error of the model was 0.3-0.8℃, and the average relative error was within 2.6%, indicating that the model has good prediction effect and can be better applied to the prediction of fish pond water temperature in summer. [ABSTRACT FROM AUTHOR]

In the summer of 2022 (June-August), the national average air temperature was 22.3°C, which was 1.1°C higher than the same period of the normal year (1991-2020). There were sufficient thermal resources in major agricultural areas. The national average high temperature days reached 14.3d, which was 6.3d more than that in the same period of from 1991 to 2020, and had been the maximum value since 1961. The national average precipitation was only 290.6mm, being the second smallest in the same period since 1961. The national average sunshine duration was 677.4h, which was close to the same period in the normal year and 53.7h more than that in 2021. The weather in most summer-harvesting areas was fine, which was conducive to the full maturity and quality improvement in grain and oil crops. There were two obvious precipitation events in late June, which effectively alleviated the previous drought in the northern summer-sowing areas. However, the deviation of soil moisture was not conducive to timely summer planting in some areas in Shaanxi and Gansu. Most of the agricultural areas were exposed to sufficient light and heat, with no occurrence of obvious cloudy and rainy weather. There was abundant precipitation and suitable soil moisture in the northern agricultural areas, which was in favor of the growth, development and yield formation for local crops such as corn and soybeans. The continuous high temperature and lack of rain in the southern agricultural areas led to the development of agricultural drought and heat stress for crops such as rice and maize. The meteorological conditions limited the stable growth of crops, economic trees and fruits. Superimposed precipitation occurred in Liaoning and Shandong, resulting in waterlogging in some lowland areas. Moreover, periodical low temperature in early June and late August affected the growth, development and grain filling of -harvesting crops in the Northeast. [ABSTRACT FROM AUTHOR]

Based on the daily national meteorological data in spring in 2022, relationships between meteorological factors and agricultural production in China were analyzed using statistical methods. The results showed that the national average air temperature in spring in 2022 was 12.1Ž, which was the highest during the same period since 1961. The national average air temperature in the first ten days and the second ten days in March, and also in the first ten days in April, was abnormally higher than the same period from 1991 to 2020. The national average air temperature in the second ten days in May was obviously lower than the same period in the normal year. The year 2022 was a typical cold year in late spring. The national average precipitation in spring in 2022 was 154.0 mm, which was more than that in the same period in the normal year. In particular, the average precipitation in Sichuan in spring this year was the most since 1961. The national average sunshine was 649.2 hours, close to the same period in the normal year. The suitable sunshine and temperature, and also good soil moisture conditions were favorable for winter wheat growth with delayed sowing date in autumn in 2021 in Northern China, and the delayed-sowing winter wheat growing conditions continued to improve and upgrade in spring in 2022. The meteorological conditions in spring in 2022 were generally conducive to winter wheat growth and yield increase per hectare. The soil moisture and temperature conditions were suitable in most of the spring sowing areas, and the influence of phased low temperature was relatively light, which was conducive to the sowing and emergence of crops in spring. The progress of spring sowing was generally faster than that of the previous year. The seedlings growed well. It was sunny during most of winter wheat mature and harvest period in southern China, and the wheat harvest progressed well. But obvious drought in western Liaoning was unfavorable to spring sowing. In the late spring, heavy rainfall occurred in the east of Jianghan, the south of Jianghuai, the west of South China and the Southwest China. There were many rainy days and little sunshine in the south of Southwest China. At the end of spring, hot and dry weather appeared in some wheat areas in Eastern North China, Huang Huai. The bad weather had a certain negative impact on spring sowing and late grain filling of winter wheat in some of the above regions. [ABSTRACT FROM AUTHOR]

In order to provide reference for vegetable growth management and environmental optimization regulation, the dynamic changes of greenhouse temperature and humidity were predicted by using ARIMA model and RBF neural network. In this study, the data from July 28 to 29 were taken as the validation set, and the data from the previous 5 to 25 days were taken as the sample set. Three input variables were set to explore the temperature and humidity model prediction effects. Based on the measured data of air temperature, relative humidity and light intensity in the vegetable greenhouse, and according to the difference in the predictive ability of ARIMA model and RBF neural network for linear and nonlinear problems, temperature and humidity prediction models based on weight combination of ARIMA and RBF neural network were constructed. The results showed that the temperature and humidity in the greenhouse had more obvious linear and nonlinear variation characteristics, respectively, and the single models with better prediction effects were the ARIMA model and the RBF model. The optimal single temperature model was the model ARIMA(0,1,1)(1,1,1) 24 with 25 days sample set. The optimal single humidity model was the RBF model (3-6-2) with 25 days sample set and input variable A (temperature, humidity and light intensity). Compared with the optimal single models, the ARIMA-RBF neural network weight combination model had higher prediction accuracy and better stability. The MAE, MAPE and RMSE were 1.04°C, 2.95%, 1.21°C for the optimal temperature combination model and 0.35 percentage point, 0.36%, 0.55 percentage point for the optimal humidity combination model. The weight combination model gives full play to the ability of single models to process data from different characteristics through an appropriate weighting strategy, and can better evaluate the temperature and humidity status in the greenhouse, which provides a reference for establishing a more universal greenhouse environmental factor model. [ABSTRACT FROM AUTHOR]

To investigate the effects of high temperature and high humidity compound disasters on leaf photosynthesis and flower sex differentiation of cucumber plants, the cucumber variety "Jinyou101" was used as the test materials. The three factors orthogonal test of air temperature, air relative humidity and treatment days was conducted in the artificial climate chamber of Nanjing University of Information Science and Technology from May to September 2020. Four levels of day/night temperature were set to 32℃/22℃, 35℃/25℃, 38℃/28℃ and 41℃/31℃. The air relative humidity was set at three levels: 50%, 70% and 90%（±5 percent point）, and the durations of treatment time were designed for 3, 6, 9 and 12 days. The treatments of day temperature 28℃/ night temperature 18℃, air relative humidity 50%±5pp were used as control (CK). The photosynthetic parameters, chlorophyll content and endogenous hormone content of terminal bud were measured systematically, and the floral differentiation of each node and final yield were observed. The results showed that: （1）the total amount of chlorophyll in cucumber leaves decreased with the increase of temperature and the extension of stress time. After 12 days of stress, chlorophyll a, chlorophyll b and carotenoid contents in cucumber leaves reached the lowest value, which decreased by 31.51%, 22.62% and 37.10% compared with CK, respectively. （2）The Pmax (maximum net photosynthetic rate), LSP (light saturation point) and AQE (apparent quantum efficiency) values of cucumber leaves decreased significantly with the deepening of high temperature and humidity stress. The LSP, AQE and Pmax values of cucumber leaves at 41℃ were the lowest, which were 48.78%, 40.00% and 43.04% lower than those of CK, respectively. In the range of 32−41℃, the Pmax values of cucumber leaves under 70% air relative humidity were higher than those under other humidity treatments, and the differences were small compared with CK. （3）In the process of flower bud differentiation, the contents of ZT (anti-zeaxin), ABA (abscisic acid) and GA3 (gibberellin) in cucumber terminal buds increased firstly and then decreased, while the contents of IAA decreased gradually with the growth of cucumber plant. The contents of ZT, IAA and GA3 in cucumber terminal buds decreased gradually with the increase of temperature and days of stress, while the changes of ABA content were on the contrary. At the end of 41℃, the contents of ZT, IAA and GA3 decreased by 47.37%, 26.38% and 83.65%, respectively, compared with CK, while the ABA content increased by 27.27% compared with CK. After 12 days of stress, the contents of ZT, IAA and GA3 reached the lowest values in the same period (0.07μg·g−1, 1.11μg·g−1, 0.75μg·g−1), while the ABA content reached the highest values in the same period (1.89μg·g−1).（4）High temperature and high humidity stress increased the node position of each female flower, but decreased the node rate of female flower and the number of flower buds. When treated with 70% air relative humidity, the nodes of female flowers were decreased, and the proportion of female flower nodes and the number of flower buds were increased. （5）High temperature and high humidity stress significantly reduced cucumber yield, and the yield of cucumber treated at 41℃ was 38.50% lower than that of CK. The study found that high temperature inhibited photosynthesis in cucumber leaves, disrupted the endogenous hormone balance in terminal buds, and reduced the number of female flower differentiation, resulting in lower final yield. [ABSTRACT FROM AUTHOR]

Three major production areas of Fuji apple, Linyi (in Shanxi province), Luochuan (in Shaanxi province) and Qixia (in Shandong province) were selected as the study region, based on 1 km gridded meteorological data, actual first flowering date data, and Chilling Hour Model (CHM) and Growing Degree Hour (GDH) data of the survey sample points in 2019-2020, the optimal chill/heat requirement at the first flowering date of apple was obtained using the gridded search method. Then, the daily air temperature characteristic values (Tmax, Tmin and Tavg) were divided into seven daily air temperature characteristic factor combinations, including single factor, double factors and triple factors, and the random forest algorithm (RF) was used to establish three regional daily chill/heat accumulation models with different daily air temperature characteristic factor combinations to select the optimal daily air temperature characteristic factor. On the basis of which, forecasting model of apple first flowering date was established based on the optimal daily air temperature characteristic factor by using RF algorithm, and the accuracy of the forecasting model was evaluated by independent actual first flowering date data. The results showed that: (1) the optimal chill/heat requirement at the first flowering date for apple in three regions were 730CH and 7350GDH in Linyi, 345CH and 4950GDH in Luochuan, and 520CH and 4450GDH in Qixia. (2) Among the seven combinations of daily air temperature characteristics, the three regional daily chill/heat accumulation models with the combination of Tmax, Tmin and Tavg had high accuracy in estimating daily chill/heat accumulation, and the RMSE between the estimated daily chill accumulation and the daily chill accumulation obtained from the CHM model was 0.97-2.50CH, and the RMSE between the estimated daily heat accumulation and the daily heat accumulation obtained from the GDH model was 1.73-15.76GDH. (3) When the daily chill/heat accumulation was estimated by forecast model of apple first flowering date, the RMSE between the estimated daily chill accumulation and the daily chill accumulation based on the CHM model ranged from 1.08 to 1.14CH, and the RMSE between the estimated daily heat accumulation and the daily heat accumulation based on the GDH model ranged from 2.03 to 3.74GDH. When the model was used to forecast first flowering date of apple, R² between the predicted and actual first flowering date was 0.92, and RMSE was 3.44d. The accuracy of the predicted first flowering date based on daily air temperature characteristic values was in overall agreement with that based on real hourly air temperature data, it indicated that the forecast model of apple flowering date established in this paper could effectively convert the input air temperature data from hourly scale to daily scale, which will have good application value and potential in the subsequent work on apple first flowering date forecasting. [ABSTRACT FROM AUTHOR]

In order to accurately estimate the reference crop evapotranspiration (ETc) of wheat using incomplete meteorological elements, three verification and analysis processes in estimation of some meteorological elements were carried out by using daily forecast weather data and the corresponding daily measured meteorological data of Xinxiang during winter wheat growing seasons from 2014 to 2016, as well as modified solar radiation parameters and adjustment coefficients. First, the accuracy of forecast air temperature was verified. Then, the actual water vapor pressure and solar radiation were estimated based on forecast air temperature. Finally, the forecast air temperature and averaged wind speed were adopted to estimate the reference ETc based on the Penman-Monteith formula. The results showed that the daily forecast air temperature could replace the daily observed air temperature, water vapor pressure and solar radiation using the forecast maximum and minimum temperature, which met the requirements of Penman-Monteith formula, and the accuracy of the radiation estimated using weather forecast data was higher than that of the aerodynamics. Generally, the accuracy of the radiation in the daily reference ETc estimated by weather forecast data was higher than that of the aerodynamics, the estimated values by weather forecast was relatively lower, and the underestimate rate was below 7%. Through statistical analysis, there was a high correlation between daily ETc estimated by weather forecast and that estimated by Penman-Monteith equation (R²=0.77). Therefore, it was feasible to use the daily meteorological data from weather forecast to estimate the reference ETc, and it was suggested to use the radiation method to estimate ETc in arid and semi-arid areas, which provided theoretical and methodological guarantee for agricultural irrigation forecast and had reference significance for guiding the optimal allocation of local agricultural water resources. [ABSTRACT FROM AUTHOR]