scholarly journals Projection in Extreme Climate Events and uncertainty analysis in the Source Area of the Yellow River for the Next Three Decades

Author(s):  
Yu Ping Han ◽  
Zi Tian Chen ◽  
Heng Xiao
Author(s):  
Zigeng Niu ◽  
Lan Feng ◽  
Xinxin Chen ◽  
Xiuping Yi

The Yellow River Basin (YLRB) and Yangtze River Basin (YZRB) are heavily populated, important grain-producing areas in China, and they are sensitive to climate change. In order to study the temporal and spatial distribution of extreme climate events in the two river basins, seven extreme temperature indices and seven extreme precipitation indices were projected for the periods of 2010–2039, 2040–2069, and 2070–2099 using data from 16 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and the delta change and reliability ensemble averaging (REA) methods were applied to obtain more robust ensemble values. First, the present evaluation indicated that the simulations satisfactorily reproduced the spatial distribution of temperature extremes, and the spatial distribution of precipitation extremes was generally suitably captured. Next, the REA values were adopted to conduct projections under different representative concentration pathway (RCP) scenarios (i.e., RCP4.5, and RCP8.5) in the 21st century. Warming extremes were projected to increase while cold events were projected to decrease, particularly on the eastern Tibetan Plateau, the Loess Plateau, and the lower reaches of the YZRB. In addition, the number of wet days (CWD) was projected to decrease in most regions of the two basins, but the highest five-day precipitation (Rx5day) and precipitation intensity (SDII) index values were projected to increase in the YZRB. The number of consecutive dry days (CDD) was projected to decrease in the northern and western regions of the two basins. Specifically, the warming trends in the two basins were correlated with altitude and atmospheric circulation patterns, and the wetting trends were related to the atmospheric water vapor content increases in summer and the strength of external radiative forcing. Notably, the magnitude of the changes in the extreme climate events was projected to increase with increasing warming targets, especially under the RCP8.5 scenario.


2017 ◽  
Vol 23 (10) ◽  
pp. 4045-4057 ◽  
Author(s):  
Ross E. Boucek ◽  
Michael R. Heithaus ◽  
Rolando Santos ◽  
Philip Stevens ◽  
Jennifer S. Rehage

2019 ◽  
Vol 96 ◽  
pp. 669-683 ◽  
Author(s):  
Enliang Guo ◽  
Jiquan Zhang ◽  
Yongfang Wang ◽  
Lai Quan ◽  
Rongju Zhang ◽  
...  

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109126 ◽  
Author(s):  
Selena Ahmed ◽  
John Richard Stepp ◽  
Colin Orians ◽  
Timothy Griffin ◽  
Corene Matyas ◽  
...  

Ecology ◽  
2019 ◽  
Vol 100 (2) ◽  
pp. e02578 ◽  
Author(s):  
Martina Dal Bello ◽  
Luca Rindi ◽  
Lisandro Benedetti‐Cecchi

Author(s):  
Dongying Yi ◽  
Yue Xu ◽  
Nan Wang ◽  
Xiaoyi Ma

The primary approach to realizing long-term runoff prediction involves combining a hydrological model with general circulation model. Previous studies on the Source area of the Yellow River were all based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) data sets with defects in physical mechanisms. In this paper, the Beijing Climate Center Climate System Model (BCC-CSM2-MR) of CMIP6, which proved to perform well in arid and semi-arid regions, will be used to drive the Soil & Water Assessment Tool (SWAT) model and evaluate its applicability in runoff simulation at Tang Nahai Hydrological Station from 2011 to 2019. The occurrence of the extreme value of runoff, its change trend, and the year of abrupt change of runoff in the four Shared Socio-economic Pathway (SSP) scenarios (SSP1-2.6, 2-4.5, 3-7.0, and 5-8.5) during 2021-2100 were analyzed. The results show that: (1) the runoff simulation evaluation index of SWAT driven by BCC-CSM2-MR in the research area from 2011 to 2019 is excellent, and the runoff simulation in the future is reliable and effective. (2) only the average annual runoff in scenario 5-8.5 (708.5m /s) from 2021 to 2100 was significantly higher than that in 2011-2019. Other scenarios are close to or less than the annual runoff observed. Most importantly, the maximum and minimum annual runoff values under the four scenarios all occurred during 2060-2080, so the attribution analysis of runoff extremum during 2060-2080 is worth further study. (3) it is necessary to evaluate whether the existing reservoirs and hydropower stations in the Yellow River basin can reasonably regulate and utilize the annual runoff under scenario 5-8.5.


2021 ◽  
Vol 15 (3) ◽  
pp. e0009182
Author(s):  
Cameron Nosrat ◽  
Jonathan Altamirano ◽  
Assaf Anyamba ◽  
Jamie M. Caldwell ◽  
Richard Damoah ◽  
...  

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983–2019 for rainfall, 2000–2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission.


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