Characterization of daily rainfall variability in Hong Kong: A nonlinear dynamic perspective

Author(s):  
Zhenru Shu ◽  
Pak Wai Chan ◽  
Qiusheng Li ◽  
Yuncheng He ◽  
Bowen Yan
2015 ◽  
Vol 143 (6) ◽  
pp. 2192-2206 ◽  
Author(s):  
Richard C. Y. Li ◽  
Wen Zhou ◽  
Tsz Cheung Lee

Abstract This study examines the climatological features of tropical cyclone (TC) rainfall in Hong Kong in association with different TC-related parameters, and investigates the changes in TC rainfall, non-TC rainfall, and total rainfall during the past few decades in Hong Kong. On average, rainfall induced by TCs can account for about 25% of the total precipitation during summer and fall, and the contribution can be even greater in extreme cases. Composite analysis suggests that extreme TC rainfall is often related to TCs in closer proximity to Hong Kong, with higher intensity, and is associated with stronger convection and moisture convergence in the vicinity of Hong Kong. Evaluations of the observed trends of different rainfall indices suggest that the rainfall variability in Hong Kong is considerably affected by the TC rainfall, which has a decreasing trend in frequency and intensity in recent decades. Taking out the TC rainfall from the total rainfall reveals that there is an increasing trend in daily rainfall frequency and intensity for non-TC rainfall in Hong Kong. Moreover, time-dependent generalized extreme value analysis of non-TC rainfall also reveals an increase in the return values of the maximum daily rainfall in Hong Kong. Results of this study suggest that, in order to obtain a more comprehensive picture of the long-term rainfall variations in Hong Kong, the contributions of TC rainfall should definitely be taken into account in the analysis.


2020 ◽  
Vol 13 (4) ◽  
pp. 1425
Author(s):  
Layara Campelo Dos Reis ◽  
Cláudio Moisés Santos e Silva ◽  
Bergson Guedes Bezerra ◽  
Maria Helena Constantino Spyrides

A análise sobre a variabilidade dos padrões climatológicos espaciais e temporais das chuvas fornecem informações valiosas para a condução de cultivos agrícolas, principalmente em condições de sequeiro. Assim, o presente estudo objetivou caracterizar a variabilidade da precipitação no MATOPIBA, região produtora de soja, sob influência das fases do ENSO e do gradiente térmico do Atlântico Tropical. Foram utilizados dados diários de precipitação do período de 1980-2013 dispostos em uma grade de espaçamento de 0,25º x 0,25°, abrangendo 963 pontos sobre a região. O acumulado mensal da precipitação foi especializado por meio de sistemas geográficos de informação e da geoestatística. A variabilidade da precipitação foi analisada por meio da aplicação do teste de Mann-Kendall, considerando três cenários de condições meteorológicas (climatologia, favorável-wet e desfavorável-dry) à ocorrência da precipitação. Os volumes de chuvas foram relativamente maiores no cenário da fase fria do ENSO combinado com o gradiente inter-hemisférico apontando para o Sul (favorável-wet), em contrapartida, verificou-se um aumento de condições de risco hídrico nos anos com ocorrência da fase quente do ENSO e o gradiente apontando para o Norte (desfavorável-dry), embora com exceções registradas em algumas áreas no mês de Janeiro e Fevereiro. Tendências positivas e negativas foram identificadas, constatando indícios de alterações nos padrões da variável, previamente para os cenários da climatologia e desfavorável (dry). Os resultados poderão contribuir para o desenvolvimento de soluções e direcionamento na tomada de decisões pelos agentes da cadeia produtiva que visem a mitigação de impactos em decorrência da variabilidade da precipitação na região estudada.  Characterization of rainfall variability in the MATOPIBA, soybean producing region AbstractThe analysis of spatial and temporal rainfall patterns variability provides invaluable information for the development of dryland agriculture systems. Therefore, the aim of the present study was to characterize the variability of rainfall in the MATOPIBA, an important soybean producing region, under the influence of ENSO phases and the tropical Atlantic thermal gradient. We used daily rainfall data for the period from 1980-2013 arranged in a 0.25º x 0.25º spacing grid, comprising 963 points over the study region. Monthly accumulated rainfall has been specialized through geographic information systems and geostatistics. Variability rainfall was analyzed by applying the Mann-Kendall test, considering three scenarios of meteorological conditions (climatology, favorable-wet and unfavorable-dry) to the occurrence of precipitation. Rainfall volumes were relatively higher in the ENSO cold phase scenario combined with the southward-favorable interhemispheric gradient. ENSO and the gradient pointing north (unfavorable-dry), although with exceptions recorded in some areas in January and February. Positive and negative trends were identified, showing evidence of changes in the variable's patterns, previously for the climatology and unfavorable (dry) scenarios. The results may contribute to the development of solutions and decision making direction by the agents of the productive chain aiming at mitigating impacts due to the variability of precipitation in the studied region.Keywords: Climate variability; ENSO; Agrometeorology  


2011 ◽  
Vol 45 (34) ◽  
pp. 6191-6196 ◽  
Author(s):  
Yu Huang ◽  
Steven Sai Hang Ho ◽  
Kin Fai Ho ◽  
Shun Cheng Lee ◽  
Yuan Gao ◽  
...  

2004 ◽  
Vol 38 (7) ◽  
pp. 963-970 ◽  
Author(s):  
Xiaohong Yao ◽  
Ming Fang ◽  
Chak K. Chan ◽  
K.F. Ho ◽  
S.C. Lee
Keyword(s):  

2011 ◽  
Vol 74 (4) ◽  
pp. 947-952 ◽  
Author(s):  
Yuan Kang ◽  
Kwai Chung Cheung ◽  
Zong Wei Cai ◽  
Ming H. Wong
Keyword(s):  

2021 ◽  
Vol 3 (8) ◽  
Author(s):  
Majid Javari

AbstractThis paper represents the recurrence (reoccurrence) changes in the rainfall series using Markov Switching models (MSM). The switching employs a dynamic pattern that allows a linear model to be combined with nonlinearity models a discrete structure. The result is the Markov Switching models (MSM) reoccurrence predicting technique. Markov Switching models (MSM) were employed to analyze rainfall reoccurrence with spatiotemporal regime probabilities. In this study, Markov Switching models (MSM) were used based on the simple exogenous probability frame by identifying a first-order Markov process for the regime probabilities. The Markov transition matrix and regime probabilities were used to analyze the rainfall reoccurrence in 167 synoptic and climatology stations. The analysis results show a low distribution from 0.0 to 0.2 (0–20%) per day spatially from selecting stations, probability mean of daily rainfall recurrence is 0.84, and a different distribution based on the second regime was found to be more remarkable to the rainfall variability. The rainfall reoccurrence in daily rainfall was estimated with relatively low variability and strong reoccurrence daily with ranged from 0.851 to 0.995 (85.1–99.5%) per day based on the spatial distribution. The variability analysis of rainfall in the intermediate and long variability and irregular variability patterns would be helpful for the rainfall variability for environmental planning.


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