Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological obse...Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological observational data in a period of two years as the reference, the maximum and minimum temperature predictions of Shenyang station from the European Center for Medium-Range Weather Forecasts (ECMWF) and national intelligent grid forecasts are objectively corrected by using wavelet analysis, sliding training and other technologies. The evaluation results show that the sliding training time window of the maximum temperature is smaller than that of the minimum temperature, and their difference is the largest in August, with a difference of 2.6 days. The objective correction product of maximum temperature shows a good performance in spring, while that of minimum temperature performs well throughout the whole year, with an accuracy improvement of 97% to 186%. The correction effect in the central plains is better than in the regions with complex terrain. As for the national intelligent grid forecasts, the objective correction products have shown positive skills in predicting the maximum temperatures in spring (the skill-score reaches 0.59) and in predicting the minimum temperature at most times of the year (the skill-score reaches 0.68).展开更多
[Objective] The research aimed to analyze temporal and spatial variation characteristics of temperature in Shangqiu City during 1961-2010.[Method] Based on temperature data in eight meteorological stations of Shangqiu...[Objective] The research aimed to analyze temporal and spatial variation characteristics of temperature in Shangqiu City during 1961-2010.[Method] Based on temperature data in eight meteorological stations of Shangqiu during 1961-2010,by using trend analysis method,the temporal and spatial evolution characteristics of annual average temperature,annual average maximum and minimum temperatures,annual extreme maximum and minimum temperatures,daily range of annual average temperature in Shangqiu City were analyzed.M-K method was used to determine mutation year of temperature.[Result] The annual average temperature,annual average minimum temperature and annual extreme minimum temperature respectively rose at 0.122,0.255 and 0.488 ℃/10 a.The variation trend of annual average maximum temperature wasn’t obvious.The daily range of annual average temperature and annual extreme maximum temperature respectively declined at-0.217 and-0.292 ℃/10 a.Seen from spatial distribution,the increase amplitudes of annual average temperature,annual average minimum temperature and annual extreme minimum temperature were all large in the east and small in the west.The decrease amplitude of daily range of annual average temperature was large in the east and small in the west.The decrease amplitude of annual extreme maximum temperature was large in the west and small in the east.The annual average maximum temperature had trends of increase and decrease.The annual average temperature,annual average minimum temperature and daily range of annual average temperature all mutated in 1997.The annual average maximum temperature didn’t have obvious mutation point.The annual extreme maximum temperature mutated in 1973.The annual extreme minimum temperature respectively mutated in 1989 and 1999.[Conclusion] The research played important guidance significances in adjustment of agricultural production structure,regional climate planning,reasonably using climate resource and replying climate change in Shangqiu City.展开更多
Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Curr...Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Currently, there is either no or scant information that describes the influence of climate changes and variability to watermelon production in Zanzibar. Thus, this study aimed to determine the influence of climate variability on the quantity of watermelon production in Zanzibar. The study used both primary and secondary datasets, which include the anecdotal information collected from interviewers’ responses from four districts of Unguja and Pemba, and climate parameters (rainfall, maximum and minimum temperature (Tmax and Tmin) acquired from Tanzania Meteorological Authority (TMA) at Zanzibar offices. Pearson correlation was used for analyzing the association between watermelon production and climate parameters, while paired t-test was applied to show the significance of the mean differences of watermelon and climate parameters for two periods of 2014-2017 and 2018-2021, respectively. Percentage changes were used to feature the extent to which the two investigated parameters affect each other. The anecdotal responses were sorted, calculated in monthly and seasonal averages, plotted and then analyzed. Results have shown a strong correlation (r = 0.8 at p ≤ 0.02, and r = 0.7) between watermelon production, Tmax and rainfall during OND, especially in Unguja, as well as Tmin during JJA (i.e. r = - 0.8 at p ≤ 0.02) in Pemba. Besides, results have shown the existence of significant differences between the means of watermelon production and climate parameter for the two stated periods, indicating that the climate parameters highly affects the watermelon production by either enhancing or declining the yields by 69% - 162% and 17% - 77%, respectively. Moreover, results have shown that respondents were aware that excess temperature intensity during dry periods can lead to high production costs due number of soil and other environmental factors. Besides the results have shown that OND seasonal rainfall and MAM Tmax had good association with watermelon production in Unguja while JJA Tmin declined the production in Pemba. Thus, the study concludes that seasonal variability of climate parameter has a significant influence on the watermelon production. The study calls for more studies on factors affecting watermelon production (e.g. soil characteristics, pest sides and manure), and recommends for climate based decision making on rain fed agricultural yields and routine monitoring of weather information.展开更多
Based on the data of monthly mean air temperature and precipitation from about 400 stations in 1951—1995.and the data of maximum and minimum air temperatures,relative humidity,total cloud cover and low-cloud cover,su...Based on the data of monthly mean air temperature and precipitation from about 400 stations in 1951—1995.and the data of maximum and minimum air temperatures,relative humidity,total cloud cover and low-cloud cover,sunshine duration,evaporation,wind speed,snow-covered days and depth,and soil temperatures in 8 layers from 0 m down to 3.2 m from 200 odd stations in 1961 —1995.the climate change and its characteristics in China in recent 45 years have been analyzed and studied comprehensively.This paper,as the first part of the work.has analyzed the climate change and regularities of such meteorological elements as mean air temperature,maximum and minimum air temperatures,precipitation,relative humidity and sunshine duration.The possible mechanism on climate change in China and the climate change and regularities of other meteorological elements will be discussed in another paper as the second part.展开更多
文摘Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological observational data in a period of two years as the reference, the maximum and minimum temperature predictions of Shenyang station from the European Center for Medium-Range Weather Forecasts (ECMWF) and national intelligent grid forecasts are objectively corrected by using wavelet analysis, sliding training and other technologies. The evaluation results show that the sliding training time window of the maximum temperature is smaller than that of the minimum temperature, and their difference is the largest in August, with a difference of 2.6 days. The objective correction product of maximum temperature shows a good performance in spring, while that of minimum temperature performs well throughout the whole year, with an accuracy improvement of 97% to 186%. The correction effect in the central plains is better than in the regions with complex terrain. As for the national intelligent grid forecasts, the objective correction products have shown positive skills in predicting the maximum temperatures in spring (the skill-score reaches 0.59) and in predicting the minimum temperature at most times of the year (the skill-score reaches 0.68).
文摘[Objective] The research aimed to analyze temporal and spatial variation characteristics of temperature in Shangqiu City during 1961-2010.[Method] Based on temperature data in eight meteorological stations of Shangqiu during 1961-2010,by using trend analysis method,the temporal and spatial evolution characteristics of annual average temperature,annual average maximum and minimum temperatures,annual extreme maximum and minimum temperatures,daily range of annual average temperature in Shangqiu City were analyzed.M-K method was used to determine mutation year of temperature.[Result] The annual average temperature,annual average minimum temperature and annual extreme minimum temperature respectively rose at 0.122,0.255 and 0.488 ℃/10 a.The variation trend of annual average maximum temperature wasn’t obvious.The daily range of annual average temperature and annual extreme maximum temperature respectively declined at-0.217 and-0.292 ℃/10 a.Seen from spatial distribution,the increase amplitudes of annual average temperature,annual average minimum temperature and annual extreme minimum temperature were all large in the east and small in the west.The decrease amplitude of daily range of annual average temperature was large in the east and small in the west.The decrease amplitude of annual extreme maximum temperature was large in the west and small in the east.The annual average maximum temperature had trends of increase and decrease.The annual average temperature,annual average minimum temperature and daily range of annual average temperature all mutated in 1997.The annual average maximum temperature didn’t have obvious mutation point.The annual extreme maximum temperature mutated in 1973.The annual extreme minimum temperature respectively mutated in 1989 and 1999.[Conclusion] The research played important guidance significances in adjustment of agricultural production structure,regional climate planning,reasonably using climate resource and replying climate change in Shangqiu City.
文摘Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Currently, there is either no or scant information that describes the influence of climate changes and variability to watermelon production in Zanzibar. Thus, this study aimed to determine the influence of climate variability on the quantity of watermelon production in Zanzibar. The study used both primary and secondary datasets, which include the anecdotal information collected from interviewers’ responses from four districts of Unguja and Pemba, and climate parameters (rainfall, maximum and minimum temperature (Tmax and Tmin) acquired from Tanzania Meteorological Authority (TMA) at Zanzibar offices. Pearson correlation was used for analyzing the association between watermelon production and climate parameters, while paired t-test was applied to show the significance of the mean differences of watermelon and climate parameters for two periods of 2014-2017 and 2018-2021, respectively. Percentage changes were used to feature the extent to which the two investigated parameters affect each other. The anecdotal responses were sorted, calculated in monthly and seasonal averages, plotted and then analyzed. Results have shown a strong correlation (r = 0.8 at p ≤ 0.02, and r = 0.7) between watermelon production, Tmax and rainfall during OND, especially in Unguja, as well as Tmin during JJA (i.e. r = - 0.8 at p ≤ 0.02) in Pemba. Besides, results have shown the existence of significant differences between the means of watermelon production and climate parameter for the two stated periods, indicating that the climate parameters highly affects the watermelon production by either enhancing or declining the yields by 69% - 162% and 17% - 77%, respectively. Moreover, results have shown that respondents were aware that excess temperature intensity during dry periods can lead to high production costs due number of soil and other environmental factors. Besides the results have shown that OND seasonal rainfall and MAM Tmax had good association with watermelon production in Unguja while JJA Tmin declined the production in Pemba. Thus, the study concludes that seasonal variability of climate parameter has a significant influence on the watermelon production. The study calls for more studies on factors affecting watermelon production (e.g. soil characteristics, pest sides and manure), and recommends for climate based decision making on rain fed agricultural yields and routine monitoring of weather information.
文摘Based on the data of monthly mean air temperature and precipitation from about 400 stations in 1951—1995.and the data of maximum and minimum air temperatures,relative humidity,total cloud cover and low-cloud cover,sunshine duration,evaporation,wind speed,snow-covered days and depth,and soil temperatures in 8 layers from 0 m down to 3.2 m from 200 odd stations in 1961 —1995.the climate change and its characteristics in China in recent 45 years have been analyzed and studied comprehensively.This paper,as the first part of the work.has analyzed the climate change and regularities of such meteorological elements as mean air temperature,maximum and minimum air temperatures,precipitation,relative humidity and sunshine duration.The possible mechanism on climate change in China and the climate change and regularities of other meteorological elements will be discussed in another paper as the second part.
