The Copula Function-Based Probability Characteristics Analysis on Seasonal Drought &amp; Flood Combination Events on the North China Plain

Mu, Wenbin; Yu, Fuliang; Xie, Yongshuai; Liu, Jia; Li, Chuanzhe; Zhao, Na

doi:10.3390/atmos5040847

Cited by 13 publications

(12 citation statements)

References 28 publications

(31 reference statements)

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“…The northeastern, eastern and southern regions are classified as having acceptable conditions (40 ≤ TCI ≤ 59). The former areas have higher TCI scores, because of the moderate temperatures and relative dry weather in spring, which are called the spring drought [39]; conversely, the low temperature is responsible for the low scores of the northeast and Tibetan Plateau, while a humid climate with abundant precipitation leads to those for the southern regions. The average TCI map during autumn shows the same categories with good and acceptable conditions during spring, and the essential difference between these two seasons is that the regions characterized as "good" stretch to eastern and southern China during autumn, which can be generally attributed to the decreasing humidity.…”

Section: Resultsmentioning

confidence: 99%

National Assessment of Climate Resources for Tourism Seasonality in China Using the Tourism Climate Index

Yan

Yin

2015

Atmosphere

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Tourism is a very important industry, and it is deeply affected by climate. This article focuses on the role of climate in tourism seasonality and attempts to assess the impacts of climate resources on China's tourism seasonality by using the Tourism Climate Index (TCI). Seasonal distribution maps of TCI scores indicate that the climates of most regions in China are comfortable for tourists during spring and autumn, while the climate conditions differ greatly in summer and winter, with "excellent", "good", "acceptable" and "unfavorable" existing almost by a latitudinal gradation. The number of good months throughout China varies from zero (the Tibetan Plateau area) to 10 (Yunnan Province), and most localities have five to eight good months. Moreover, all locations in China can be classified as winter peak, summer peak and bi-modal shoulder peak. The results will provide some useful information for tourist destinations, travel agencies, tourism authorities and tourists.

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Section: Resultsmentioning

confidence: 99%

National Assessment of Climate Resources for Tourism Seasonality in China Using the Tourism Climate Index

Yan

Yin

2015

Atmosphere

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“…The applications of copula models have increased over time due to their flexibility and recently got special attention in the areas of finance, climatology, actuarial science, hydrology, medicine, psychology, econometrics and currently also in atmospheric sciences where multivariate normality is in question (Vrac et al ., ; Kole et al ., ; Yan, ; Chiou and Tsay, ; Brechmann and Schepsmeier, ; Aghakouchak, ; Mu et al ., ). The spatial dependence structure plays an important role in understanding the effects of climatology and studying its impacts on hydrology, agriculture, forestry and so forth.…”

Section: Introductionmentioning

confidence: 97%

A novel approach for modelling pattern and spatial dependence structures between climate variables by combining mixture models with copula models

Khan

Spöck

Pilz

2019

Intl Journal of Climatology

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Spatiotemporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or subbasin. This further affects the hydrological conditions and, consequently, will provide misleading results if these structures are not taken into account properly. In this study, we modelled the spatial dependence structure of three climate variables, maximum and minimum temperature and precipitation, throughout the Monsoon‐dominated zone of Pakistan. For temperature, six meteorological stations have been considered, for precipitation we used the results of four meteorological stations. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C‐Vine, D‐Vine and student t‐copula models. For temperature, multivariate mixture normal distributions, and for precipitation, the gamma distribution, have been used as marginals under the copula models. The models were calibrated by utilizing the 20 years daily data from 1981 to 2000, and for validation, we used the data for 10‐year period from 2001 to 2010. The simulations were performed for each variable separately, conditioned on spatial neighbours. A comparison was made between the different copula models, on the basis of observational and simulated patterns and spatial dependence structures, the performance was evaluated for the validation period. The results show that all copula models performed well; however, there are subtle differences between them. The copula models captured the patterns and spatial dependence structures between climate variables, however, the t‐copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except a few maximum values for maximum temperature and minimum values for minimum temperature. Probability density functions of simulated data follow closely the pattern of observational data. These methods can be combined with statistical downscaling models to improve their performance, particularly in modelling the dependence structure between climate variables at multiple sites.

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“…The advantage of the Copula is that it can construct a joint probability distribution between any two variables without considering the marginal distribution of each variable. Normally, the Copula method was applied in the research of different drought characteristics like duration and severity [31][32][33][34]. Considering the independence of the marginal distribution, it can be used to explore the probability of the co-occurrence of two variables that may have potential connections.…”

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confidence: 99%

Drought Characteristics and Its Response to the Global Climate Variability in the Yangtze River Basin, China

Huang

Fan

2018

Water

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The frequent occurrence of drought events in humid and semi-humid regions is closely related to the global climate variability (GCV). In this study, the Standard Precipitation Evapotranspiration Index (SPEI) was taken as an index to investigate the drought in the Yangtze River Basin (YRB), a typical humid and semi-humid region in China. Furthermore, nine GCV indices, such as North Atlantic Oscillation (NAO) were taken to characterize the GCV. Correlation analysis and a joint probability distribution model were used to explore the relationship between the drought events and the GCV. The results demonstrated that there were six significant spatiotemporal modes revealed by SPEI3 (i.e., seasonal drought), which were consistent with the distribution of the main sub basins in the YRB, indicating a heterogeneity of drought regime. However, the SPEI12 (i.e., annual drought) can only reveal five modes. Precipitation Indices and El Niño/Southern Oscillation (ENSO) Indices were more closely related to the drought events. A causal relationship existed between ENSO precipitation index (ESPI), NAO, East Central Tropical Pacific Sea Surface Temperature (Nino3.4) and Northern Oscillation Index (NOI) and drought in the YRB, respectively. Drought events were most sensitive to the low NAO and high NOI events. This study shows a great significance for the understanding of spatiotemporal characteristics of meteorological drought and will provide a reference for the further formulation of water resources policy and the prevention of drought disasters.tropical Pacific phenomenon worldwide. A number of studies have confirmed that there were connections between ENSO and regional climate extremes like floods and droughts [14]. A concern exists that the ongoing global warming may increase the severity of droughts and many studies have shown that drought severity increases with temperature rise [10,[15][16][17][18]. For instance, from 1972 to 2004, the warming increased global dry areas by 20% to 38% [15]. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report [19] proposed a continuous increase in global mean surface air temperature during the 21st century owing to the increase of anthropogenic greenhouse gas concentration [20], indicating an increase in drought frequency, severity and spatial extension in future.Drought can be characterized by many indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) [21][22][23]. PDSI and SPI have a wide range of applications, but each of them has its limitations. PDSI takes account of changes in surface water balance so that it is suitable for the measurement of long-term drought conditions, but the acquisition is difficult because the calculation process is complex, and the time scale is limited [24]. SPI takes precipitation as a factor. Although its calculation method is simple and time scale is flexible, it does not consider temperature, evapotranspiration and other influe...

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The Copula Function-Based Probability Characteristics Analysis on Seasonal Drought & Flood Combination Events on the North China Plain

Cited by 13 publications

References 28 publications

National Assessment of Climate Resources for Tourism Seasonality in China Using the Tourism Climate Index

National Assessment of Climate Resources for Tourism Seasonality in China Using the Tourism Climate Index

A novel approach for modelling pattern and spatial dependence structures between climate variables by combining mixture models with copula models

Drought Characteristics and Its Response to the Global Climate Variability in the Yangtze River Basin, China

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