Assessment on variability of extreme climate events for the Upper Thames River basin in Canada

2011 ◽  
Vol 26 (4) ◽  
pp. 485-499 ◽  
Author(s):  
Hyung-Il Eum ◽  
Slobodan P. Simonovic
Keyword(s):  
River Basin ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Thames River ◽  
Climate Events

Changes in extreme climate events in eastern China during 1960–2013: A case study of the Huaihe River Basin

2015 ◽  
Vol 380-381 ◽  
pp. 22-34 ◽  
Author(s):  
Wei Zhang ◽  
Shaoming Pan ◽  
Liguo Cao ◽  
Xun Cai ◽  
Kexin Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Eastern China ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
The Huaihe River ◽  
Climate Events

scholarly journals Evaluation and Future Projection of Extreme Climate Events in the Yellow River Basin and Yangtze River Basin in China Using Ensembled CMIP5 Models Data

2021 ◽  
Vol 18 (11) ◽  
pp. 6029
Author(s):  
Zigeng Niu ◽  
Lan Feng ◽  
Xinxin Chen ◽  
Xiuping Yi
Keyword(s):  
Spatial Distribution ◽  
River Basin ◽  
Yellow River ◽  
Yangtze River Basin ◽  
Yellow River Basin ◽  
Cmip5 Models ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
The Yellow River Basin ◽  
Climate Events

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.

scholarly journals Drought and Flood Monitoring of the Liao River Basin in Northeast China Using Extended GRACE Data

2018 ◽  
Vol 10 (8) ◽  
pp. 1168 ◽  
Author(s):  
Xuhui Chen ◽  
Jinbao Jiang ◽  
Hui Li
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Hydrological Cycle ◽  
Deep Understanding ◽  
General Regression Neural Network ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Drought And Flood ◽  
Terrestrial Water ◽  
Climate Events

In recent years, alternating periods of floods and droughts, possibly related to climate change and/or human activity, have occurred in the Liao River Basin of China. To monitor and gain a deep understanding of the frequency and severity of the hydro-meteorological extreme events in the Liao River Basin in the past 30 years, the total storage deficit index (TSDI) is established by the Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage anomalies (TWSAs) and the general regression neural network (GRNN)-predicted TWSA. Results indicate that the GRNN model trained with GRACE-based TWSA, model-simulated soil moisture, and precipitation observations was optimal, and the correlation coefficient and the root mean square error (RMSE) of the predicted TWSA and GRACE TWSA for the testing period equal 0.90 and 18 mm, respectively. The drought and flood conditions monitored by the TSDI were consistent with those of previous studies and records. The extreme climate events could indirectly reflect the status of the regional hydrological cycle. By monitoring the extreme climate events in the study area with TSDI, which was based on the TWSA of GRACE and GRNN, the decision of water resource management in the Liao River Basin could be made reasonably.

Can animal habitat use patterns influence their vulnerability to extreme climate events? An estuarine sportfish case study

2017 ◽  
Vol 23 (10) ◽  
pp. 4045-4057 ◽  
Author(s):  
Ross E. Boucek ◽  
Michael R. Heithaus ◽  
Rolando Santos ◽  
Philip Stevens ◽  
Jennifer S. Rehage
Keyword(s):  
Habitat Use ◽  
Extreme Climate Events ◽  
Use Patterns ◽  
Extreme Climate ◽  
Climate Events ◽  
Animal Habitat

Spatiotemporal variations of extreme climate events in Northeast China during 1960–2014

2019 ◽  
Vol 96 ◽  
pp. 669-683 ◽  
Author(s):  
Enliang Guo ◽  
Jiquan Zhang ◽  
Yongfang Wang ◽  
Lai Quan ◽  
Rongju Zhang ◽  
...  
Keyword(s):  
Northeast China ◽  
Spatiotemporal Variations ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Climate Events
Sign in / Sign up

Export Citation Format

Share Document