scholarly journals Changes in precipitation amounts and extremes across Xinjiang (northwest China) and their connection to climate indices

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10792
Author(s):  
Wenfeng Hu ◽  
Junqiang Yao ◽  
Qing He ◽  
Jing Chen
Keyword(s):  
Extreme Precipitation ◽  
Atlantic Multidecadal Oscillation ◽  
Northwest China ◽  
Distribution Functions ◽  
Climate Indices ◽  
Northern Xinjiang ◽  
Daily Precipitation Data ◽  
Multivariate Enso Index ◽  
Cross Wavelet Analysis ◽  
Periodic Changes

Xinjiang is a major part of China’s arid region and its water resource is extremely scarcity. The change in precipitation amounts and extremes is of significant importance for the reliable management of regional water resources in this region. Thus, this study explored the spatiotemporal changes in extreme precipitation using the Mann–Kendall (M–K) trend analysis, mutation test, and probability distribution functions, based on the observed daily precipitation data from 89 weather stations in Xinjiang, China during 1961–2018. We also examined the correlations between extreme precipitation and climate indices using the cross-wavelet analysis. The results indicated that the climate in Xinjiang is becoming wetter and the intensity and frequency of extreme precipitation has begun to strengthen, with these trends being more obvious after the 1990s. Extreme precipitation trends displayed spatial heterogeneity in Xinjiang. Extreme precipitation was mainly concentrated in mountainous areas, northern Xinjiang, and western Xinjiang. The significant increasing trend of extreme precipitation was also concentrated in the Tianshan Mountains and in northern Xinjiang. In addition, the climate indices, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Multivariate ENSO Index and Indian Ocean Dipole Index had obvious relationships with extreme precipitation in Xinjiang. The relationships between the extreme precipitation and climate indices were not clearly positive or negative, with many correlations advanced or delayed in phase. At the same time, extreme precipitation displayed periodic changes, with a frequency of approximately 1–3 or 4–7 years. These periodic changes were more obvious after the 1990s; however, the exact mechanisms involved in this require further study.

scholarly journals Changes in annual maximum number of consecutive dry and wet days during 1961–2008 in Xinjiang, China

2012 ◽  
Vol 12 (5) ◽  
pp. 1353-1365 ◽  
Author(s):  
Y. Zhang ◽  
F. Jiang ◽  
W. Wei ◽  
M. Liu ◽  
W. Wang ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Extreme Precipitation ◽  
Goodness Of Fit ◽  
Northwest China ◽  
Distribution Functions ◽  
Annual Maximum ◽  
Extreme Precipitation Events ◽  
Rate Of Increase ◽  
Floods And Droughts ◽  
Precipitation Events

Abstract. Extreme precipitation events are major causes of severe floods and droughts worldwide. Therefore, scientific understanding of changing properties of extreme precipitation events is of great scientific and practical merit in the development of human mitigation of natural hazards, such as floods and droughts. Wetness and dryness variations during 1961–2008 in Xinjiang, a region of northwest China characterised by an arid climate, are thoroughly investigated using two extreme precipitation indices. These are annual maximum consecutive dry days (CDD) and annual maximum consecutive wet days (CWD), based on a daily precipitation dataset extracted from 51 meteorological stations across Xinjiang. As a result, we present spatial distributions of mean annual CDD and mean annual CWD and their trends within the study period. The results indicate that: (1) CDD maximize in the Taklimakan and Turban basins of southeast Xinjiang, while minima are found in the Tianshan Mountains and the Ili river valley of northwest Xinjiang. On the contrary, the longest CWD are observed in northwest Xinjiang and the shortest in the southeast part of the region. (2) On an annual basis, CWD temporal variability shows statistically positive trends and a rate of increase of 0.1d/10a. CDD temporal variability shows statistically negative trends and a rate of decrease of 1.7d/10a. (3) Goodness-of-fit analysis for three candidate probability distribution functions, generalised Pareto distribution (GPD), generalised extreme value (GEV) and Gumbel, in terms of probability behaviours of CDD and CWD, indicates that the GEV can well depict changes of CDD and CWD. (4) The CDD and CWD better describe wet and dry conditions than precipitation in the Xinjiang. The results pave the way for scientific evaluation of dryness/wetness variability under the influence of changing climate over the Xinjiang region.

scholarly journals Patterns of Extreme Precipitation and Characteristics of Related Systems in the Northern Xinjiang Region

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 358
Author(s):  
Rui Xu ◽  
Jie Ming
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Principal Component ◽  
Reanalysis Data ◽  
Water Vapor Transport ◽  
Northern Xinjiang ◽  
The North ◽  
Western Tianshan ◽  
Daily Precipitation Data

Based on 40 years of daily precipitation, 272 extreme precipitation days in the Northern Xinjiang region are defined. Using the daily precipitation data on these days, four precipitation spatial patterns were obtained through principal component analysis. Then, daily-averaged reanalysis data were used to analyze the variations of synoptic systems on extreme precipitation days and the two days before and after. The rainfall centers shifted with the influential systems at 500 hPa. Water vapor of the western Tianshan type (Type WT) and the north of Northern Xinjiang type (Type NN) comes from the west, while vapor of the Central Tianshan type (Type CT) mainly comes from the east. In the east of Northern Xinjiang type (Type EN), water vapor converges from both sides. The centers of the upper-level jets are located west of 80° E in Type WT and CT. However, they are to the east of 80° E in the other types. This article summarizes the variations of the systems at 500 hPa, the South Asia High, the westerly jet, and the water vapor transport between the surface and 500 hPa in four types of patterns, and builds the conceptual model for each type. The models built can be applied to the heavy rainfall forecast of Northern Xinjiang.

Spatiotemporal Changes in Precipitation Extremes over Canada and Their Teleconnections to Large-Scale Climate Patterns

2019 ◽  
Vol 20 (2) ◽  
pp. 275-296 ◽  
Author(s):  
Yang Yang ◽  
Thian Yew Gan ◽  
Xuezhi Tan
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Specific Humidity ◽  
Climate Indices ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Climate Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

Abstract In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative.

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

scholarly journals How to use empirical data to improve transportation infrastructure risk assessment

2021 ◽  
Author(s):  
Weihua Zhu ◽  
Kai Liu ◽  
Ming Wang ◽  
Sadhana Nirandjan ◽  
Elco Koks
Keyword(s):  
Empirical Data ◽  
National Level ◽  
Northwest China ◽  
Mean Value ◽  
Transportation Infrastructure ◽  
Risk Assessments ◽  
Railway Infrastructure ◽  
Daily Precipitation Data ◽  
Expected Annual Damage ◽  
Exposure Distribution

Abstract. Rainfall-induced hazards, such as landslides, debris flows, and floods cause significant damage to transportation infrastructure. However, an accurate assessment of rainfall-induced hazard risk to transportation infrastructure is limited by the lack of regional and asset-tailored vulnerability curves. This study aims to use multi-source empirical damage data to generate vulnerability curves and assess the risk of transportation infrastructure to rainfall-induced hazards. The methodology is exemplified through a case study for the Chinese national railway infrastructure. In doing so, regional and national-level vulnerability curves are derived based on historical railway damage records. This is combined with daily precipitation data and the railway infrastructure market value to estimate regional- and national-level risk. The results show large variations in the shape of the vulnerability curves across the different regions. The railway infrastructure in Northeast and Northwest China is more vulnerable to rainfall-induced hazards due to low protection standards. The expected annual damage (EAD) ranges from 1.88 to 5.98 billion RMB for the Chinese railway infrastructure, with a mean value of 3.91 billion RMB. However, the risk of railway infrastructure in China shows high spatial differences due to the spatially uneven precipitation characteristics, exposure distribution, and vulnerability curves. The South, East and Central provinces have a high risk to rainfall-induced hazards, resulting in an average EAD of 184 million RMB, 176 and 156 million RMB, respectively, whereas the risk in the Northeast and Northwest provinces are estimated to be relatively lower. The usage of multi-source empirical data offer opportunities to perform risk assessments that include spatial detail among regions. These risk assessments are highly needed in order to make effective decisions to make our infrastructure resilient.

scholarly journals Features of Extreme Precipitation at Progress Station, Antarctica

2018 ◽  
Vol 31 (22) ◽  
pp. 9087-9105 ◽  
Author(s):  
Lejiang Yu ◽  
Qinghua Yang ◽  
Timo Vihma ◽  
Svetlana Jagovkina ◽  
Jiping Liu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Dynamic Processes ◽  
Annual Number ◽  
Positive Trend ◽  
Self Organizing Maps ◽  
Dipole Structure ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Precipitation Events

Observed daily precipitation data were used to investigate the characteristics of precipitation at Antarctic Progress Station and synoptic patterns associated with extreme precipitation events during the period 2003–16. The annual precipitation, annual number of extreme precipitation events, and amount of precipitation during the extreme events have positive trends. The distribution of precipitation at Progress Station is heavily skewed with a long tail of extreme dry days and a high peak of extreme wet days. The synoptic pattern associated with extreme precipitation events is a dipole structure of negative and positive height anomalies to the west and east of Progress Station, respectively, resulting in water vapor advection to the station. For the first time, we apply self-organizing maps (SOMs) to examine thermodynamic and dynamic perspectives of trends in the frequency of occurrence of Antarctic extreme precipitation events. The changes in thermodynamic (noncirculation) processes explain 80% of the trend, followed by the changes in the interaction between thermodynamic and dynamic processes, which account for nearly 25% of the trend. The changes in dynamic processes make a negative (less than 5%) contribution to the trend. The positive trend in total column water vapor over the Southern Ocean explains the change of thermodynamic term.

scholarly journals Temporal and Spatial Variations of Precipitation Change from Southeast to Northwest China during the Period 1961–2017

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2622
Author(s):  
Zhu Li ◽  
Honghu Liu
Keyword(s):  
Daily Precipitation ◽  
Global Climate ◽  
Heavy Rain ◽  
Northwest China ◽  
Annual Rainfall ◽  
Trend Test ◽  
Spatiotemporal Variations ◽  
Light Rain ◽  
Daily Precipitation Data ◽  
Northwest Region

Global climate change is significant, and the spatiotemporal variations of precipitation associated with it are pronounced. Based on the daily precipitation data from 10 weather stations located from southeast to northwest across China from 1961–2017, the Mann–Kendall trend test was generally applied to analyze the spatiotemporal variations of precipitation. The factors influencing the precipitation changes were investigated. The results revealed that (1) the annual, summer, and winter rainfall amount (RA) exhibited increasing rates of 16.36, 12.31, and 2.49 mm/10 year, respectively. The change rates of annual rainfall days (RD) were 2.68 day/10 year in the northwest region and −1.88 day/10 year in the southeast. The annual and seasonal daily precipitation on rainy days (RP) exhibited an increasing trend. (2) All of the RA, RD, and RP values initially increased, then decreased, and then slightly increased from Southeast to Northwest China. These results proved that the RA increased with the increase of light rain in Northwest China and heavy rain in Southeast China. In addition, changes in the monsoon have altered the rate at which RA, RD, and RP vary with distance from the sea. These findings may help to provide suggestions for the rational spatial utilization of water resources in China.

scholarly journals Can We Expect More Extreme Precipitation on the Monthly Time Scale?

2006 ◽  
Vol 19 (4) ◽  
pp. 630-637 ◽  
Author(s):  
Rasmus E. Benestad
Keyword(s):  
Extreme Precipitation ◽  
Climate Model ◽  
Global Climate Model ◽  
Distribution Functions ◽  
Monthly Precipitation ◽  
High Latitudes ◽  
Assessment Report ◽  
The Past ◽  
Ipcc Report ◽  
Instrumental Records

Abstract The Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report states that instrumental records show an increase in precipitation by +0.5%–1% decade−1 in much of the Northern Hemisphere mid- and high latitudes and a decrease of −0.3% decade−1 over subtropical land areas. It has been postulated that these trends are associated with the enhanced levels of atmospheric CO2. In this context, it is natural to ask how continuing rising levels of CO2 may affect the climate in the future. The past IPCC reports have documented numerous studies where increased greenhouse gas concentrations have been prescribed in global climate model simulations. Now, new simulations with state-of-the-art climate models are becoming available for the next IPCC report [the Fourth Assessment Report (AR4)], and results from a number of these simulations are examined in order to determine whether they indicate a change in extreme precipitation on a monthly basis. The analysis involves a simple record–statistics framework and shows that the upper tails of the probability distribution functions for monthly precipitation are being stretched in the mid- and high latitudes where mean-level precipitation increases have already been reported in the past. In other words, values corresponding to extreme monthly precipitation in the past are, according to these results, becoming more frequent.

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