Anomalous characteristics of the atmospheric water cycle structure are highly significant to the mechanisms of seasonal-scale meteorological droughts.They also play an important role in the identification of indicativ...Anomalous characteristics of the atmospheric water cycle structure are highly significant to the mechanisms of seasonal-scale meteorological droughts.They also play an important role in the identification of indicative predictors of droughts.To better understand the causes of seasonal meteorological droughts in the middle and lower reaches of the Yangtze River(MLRYR),characteristics of the atmospheric water cycle structure at different drought stages were determined using standardized anomalies.The results showed that the total column water vapor(TCWV)was anomalously low during drought occurrence periods.In contrast,there were no anomalous signals at the drought persistence and recovery stages in the MLRYR.Moreover,there was no significant temporal correlation between the TCWV anomaly and seasonal-scale drought index(the 3-month standardized precipitation index(SPI_(3))).During drought events,water vapor that mainly originated from the Bay of Bengal was transported southwest of the MLRYR.Meanwhile,the anomalous signal of water vapor transport was negative at the drought appearance stage.At the drought persistence stage,the negative anomalous signal was the most significant.Water vapor flux divergence in the MLRYR showed significant positive anomalous signals during drought events,and the signal intensity shifted from an increasing to a decreasing trend at different drought stages.In addition,a significant positive correlation existed between the anomaly of water vapor flux divergence and regional SPI_(3).Overall,water vapor flux divergence is more predictive of droughts in the MLRYR.展开更多
[Objective]The research aimed to analyze the first soaking rain process in Lanzhou in 2011.[Method]By diagnostic analyses on weather scale,meso-scale system and physical quantity when the first soaking rain weather ha...[Objective]The research aimed to analyze the first soaking rain process in Lanzhou in 2011.[Method]By diagnostic analyses on weather scale,meso-scale system and physical quantity when the first soaking rain weather happened in Lanzhou City in 2011,formation reason and physical quantity characteristics of the soaking rain weather were discussed.[Result]Combination of the plateau low vortex and westerly cold trough was influence system of the first soaking rain.There was a southwest-southeast airflow from Sichuan Basin to Hexi in front of the trough at 700 hPa.It was commonly referred to as ＂ inverted-buckle wind＂,and provided sufficient water vapour for occurrence and maintaining of the precipitation.Convergence at the low layer and divergence at the high layer were favourable for vertical motion.Analyses on physical quantity and meso-scale system also proved important role of the ＂ inverted-buckle wind＂ at the low layer.[Conclusion]The research provided reference for real-time forecast business of the long drought turning rain in spring.展开更多
Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other ...Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.展开更多
基金supported by the National Key Research and Development Program of China(Grants No.2019YFC0409000,2017YFC1502403,and 2018YFC0407701)the Fundamental Research Funds for the Central Universities(Grant No.B200204045).
文摘Anomalous characteristics of the atmospheric water cycle structure are highly significant to the mechanisms of seasonal-scale meteorological droughts.They also play an important role in the identification of indicative predictors of droughts.To better understand the causes of seasonal meteorological droughts in the middle and lower reaches of the Yangtze River(MLRYR),characteristics of the atmospheric water cycle structure at different drought stages were determined using standardized anomalies.The results showed that the total column water vapor(TCWV)was anomalously low during drought occurrence periods.In contrast,there were no anomalous signals at the drought persistence and recovery stages in the MLRYR.Moreover,there was no significant temporal correlation between the TCWV anomaly and seasonal-scale drought index(the 3-month standardized precipitation index(SPI_(3))).During drought events,water vapor that mainly originated from the Bay of Bengal was transported southwest of the MLRYR.Meanwhile,the anomalous signal of water vapor transport was negative at the drought appearance stage.At the drought persistence stage,the negative anomalous signal was the most significant.Water vapor flux divergence in the MLRYR showed significant positive anomalous signals during drought events,and the signal intensity shifted from an increasing to a decreasing trend at different drought stages.In addition,a significant positive correlation existed between the anomaly of water vapor flux divergence and regional SPI_(3).Overall,water vapor flux divergence is more predictive of droughts in the MLRYR.
文摘[Objective]The research aimed to analyze the first soaking rain process in Lanzhou in 2011.[Method]By diagnostic analyses on weather scale,meso-scale system and physical quantity when the first soaking rain weather happened in Lanzhou City in 2011,formation reason and physical quantity characteristics of the soaking rain weather were discussed.[Result]Combination of the plateau low vortex and westerly cold trough was influence system of the first soaking rain.There was a southwest-southeast airflow from Sichuan Basin to Hexi in front of the trough at 700 hPa.It was commonly referred to as ＂ inverted-buckle wind＂,and provided sufficient water vapour for occurrence and maintaining of the precipitation.Convergence at the low layer and divergence at the high layer were favourable for vertical motion.Analyses on physical quantity and meso-scale system also proved important role of the ＂ inverted-buckle wind＂ at the low layer.[Conclusion]The research provided reference for real-time forecast business of the long drought turning rain in spring.
文摘Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.
