scholarly journals The Seesaw of Seasonal Precipitation Variability between North China and the Southwest United States, a Response to Arctic Amplification

2021 ◽  
Author(s):  
Haijin Dai ◽  
Jun Zhao ◽  
Qiang Yao ◽  
Xueyan Zhang
Keyword(s):  
United States ◽  
North China ◽  
Precipitation Variability ◽  
Seasonal Precipitation ◽  
Arctic Amplification ◽  
Southwest United States

scholarly journals Interdecadal Seesaw of Precipitation Variability between North China and the Southwest United States

2019 ◽  
Vol 32 (10) ◽  
pp. 2951-2968 ◽  
Author(s):  
Qing Yang ◽  
Zhuguo Ma ◽  
Peili Wu ◽  
Nicholas P. Klingaman ◽  
Lixia Zhang
Keyword(s):  
United States ◽  
North Pacific ◽  
Large Scale ◽  
North China ◽  
Atlantic Multidecadal Oscillation ◽  
Precipitation Variability ◽  
Circulation Anomaly ◽  
Potential Predictability ◽  
Southwest United States ◽  
Rainfall Anomalies

Abstract This paper reports a consistent seesaw relationship between interdecadal precipitation variability over North China and the Southwest United States, which can be found in observations and simulations with several models. Idealized model simulations suggest the seesaw could be mainly driven by the interdecadal Pacific oscillation (IPO), through a large-scale circulation anomaly occupying the entire northern North Pacific, while the Atlantic multidecadal oscillation (AMO) contributes oppositely and less. Modulation of precipitation by the IPO tends to be intensified when the AMO is in the opposite phase, but weakened when the AMO is in the same phase. The warm IPO phase is associated with an anomalous cyclone over the northern North Pacific; consequently, anomalous southwesterly winds bring more moisture and rainfall to the Southwest United States, while northwesterly wind anomalies prevail over North China with negative rainfall anomalies. The east–west seesaw of rainfall anomalies reverses sign when the circulation anomaly becomes anticyclonic during the cold IPO phase. The IPO-related tropical SST anomalies affect the meridional temperature gradient over the North Pacific and adjacent regions and the mean meridional circulation. In the northern North Pacific, the atmospheric response to IPO forcing imposes an equivalent barotropic structure throughout the troposphere. An important implication from this study is the potential predictability of drought-related water stresses over these arid and semiarid regions, with the progress of our understanding and prediction of the IPO and AMO.

Seasonal precipitation variability in mainland China based on entropy theory

2021 ◽  
Author(s):  
Guocan Wu ◽  
Shun Qin ◽  
Chengcheng Huang ◽  
Zhanshan Ma ◽  
Chunming Shi
Keyword(s):  
Mainland China ◽  
Precipitation Variability ◽  
Seasonal Precipitation ◽  
Entropy Theory

Understanding grower perceptions and attitudes on the use of nontraditional water sources, including reclaimed or recycled water, in the semi-arid Southwest United States

2019 ◽  
Vol 170 ◽  
pp. 500-509 ◽  
Author(s):  
Jessica L. Dery ◽  
Channah M. Rock ◽  
Rachel Rosenberg Goldstein ◽  
Cathy Onumajuru ◽  
Natalie Brassill ◽  
...  
Keyword(s):  
United States ◽  
Water Sources ◽  
Recycled Water ◽  
Southwest United States ◽  
Perceptions And Attitudes ◽  
Arid Southwest ◽  
Semi Arid

scholarly journals ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion
Keyword(s):  
United States ◽  
West Coast ◽  
Extreme Precipitation ◽  
East Coast ◽  
Daily Precipitation ◽  
Precipitation Variability ◽  
The West ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

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