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 ◽  
...  

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.

2018 ◽  
Vol 18 (7) ◽  
pp. 2047-2056 ◽  
Author(s):  
Stefan Brönnimann ◽  
Jan Rajczak ◽  
Erich M. Fischer ◽  
Christoph C. Raible ◽  
Marco Rohrer ◽  
...  

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius–Clapeyron relation, whereas weaker events or precipitation averages increase at a smaller rate than expected from the Clausius–Clapeyron relation. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present, and future. In order to make the data comparable, they are quantile mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 years and an increase of 10 %–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius–Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early autumn, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behaviour more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during the hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.


2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yanwei Zhang ◽  
Quansheng Ge ◽  
Minzhe Liu

This study focuses on extreme precipitation changes in Xinjiang Province of Northwest China, which has experienced an increase in climate disasters in recent years. This paper investigates extreme precipitation events in Xinjiang, using 54 stations with daily precipitation records from the period 1961–2008. Different statistical tests and approaches were used to check the significance of trends of single and Xinjiang regionally aggregated precipitation series for intensity and in frequency. There were predominantly positive trends in annual maximum precipitation and a remarkable increment in the frequency of extreme precipitation over certain thresholds (from 10 to 40 mm). Although the series of frequencies exceeding thresholds had positive trends, only a minority were statistically significant. This lack of significance is because of the high variability of extreme precipitation in space and time. Thus, significant trends were evident when we assessed the extreme precipitation indicators of intensity and frequency at the regional level, both in intensity and frequency over thresholds, with a clearer signal in Xinjiang.


2015 ◽  
Vol 54 (5) ◽  
pp. 979-995 ◽  
Author(s):  
Yaping Zhou ◽  
William K. M. Lau ◽  
George J. Huffman

AbstractA prototype online extreme precipitation monitoring system is developed from the TRMM TMPA near-real-time precipitation product. The system utilizes estimated equivalent average recurrence interval (ARI) for up-to-date precipitation accumulations from the past 1, 2, 3, 5, 7, and 10 days to locate locally severe events. The mapping of precipitation accumulations into ARI is based on local statistics fitted into generalized extreme value (GEV) distribution functions. Initial evaluation shows that the system captures historic extreme precipitation events quite well. The system provides additional rarity information for ongoing precipitation events based on local climatology that could be used by the general public and decision makers for various hazard management applications. Limitations of the TRMM ARI due to short record length and data accuracy are assessed through comparison with long-term high-resolution gauge-based rainfall datasets from the NOAA Climate Prediction Center and the Asian Precipitation–Highly-Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE) project. TMPA-based extreme climatology captures extreme distribution patterns from gauge data, but a strong tendency to overestimate from TMPA over regimes of complex orography exists.


2018 ◽  
Author(s):  
Stefan Brönnimann ◽  
Jan Rajczak ◽  
Erich Fischer ◽  
Christoph C. Raible ◽  
Marco Rohrer ◽  
...  

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius-Clapeyron relation, whereas weaker events or precipitation averages do not. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present and future. In order to make the data comparable, they are quantile-mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 yrs and an increase of 10–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius-Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early fall, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behavior more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.


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