scholarly journals Observed Trends in Summertime Precipitation over the Southwestern United States

2010 ◽  
Vol 23 (7) ◽  
pp. 1937-1944 ◽  
Author(s):  
Bruce T. Anderson ◽  
Jingyun Wang ◽  
Guido Salvucci ◽  
Suchi Gopal ◽  
Shafiqul Islam

Abstract In this paper, the authors evaluate the significance of multidecadal trends in seasonal-mean summertime precipitation and precipitation characteristics over the southwestern United States using stochastic, chain-dependent daily rainfall models. Unlike annual-mean precipitation, trends during the summertime monsoon, covering the period 1931–2000, indicate an overall increase in seasonal precipitation, the number of rainfall events, and the coverage of rainfall events in peripheral regions north of the “core” monsoon area of Arizona and western New Mexico. In addition, there is an increasing trend in intense storm activity and a decreasing trend in extreme dry-spell lengths. Over other regions of the domain, there are no discernible trends found in any of the observed characteristics. These trends are robust to the choice of start dates and, in the case of seasonal-mean precipitation, appear to persist into the current century.

2007 ◽  
Vol 8 (4) ◽  
pp. 938-951 ◽  
Author(s):  
Jingyun Wang ◽  
Bruce T. Anderson ◽  
Guido D. Salvucci

Abstract The intraseasonal variability of summertime precipitation over the southwestern United States is examined using stochastic daily occurrence models combined with empirical daily rainfall distributions to document 1) the seasonal evolution of the frequency and intensity of rainfall events across the summertime monsoon season and 2) the climatological evolution of wet spells, dry spells, and storm events. Study results indicate that the evolution of the North American monsoon system (NAMS) is most apparent in the occurrence of daily rainfall events, which exhibit clear time dependence across the summer season over the southwestern United States and can be principally portrayed by stochastic models. In contrast, the seasonal evolution of NAMS is largely absent in the averaged daily rainfall amount time series. There is also a significant seasonal evolution in the length of dry spells. In the central area of the domain (approximately 39 out of 78 stations) dry-spell lengths tend to increase over the course of the summer season, while on the western fringe (8 out of 78 stations) dry-spell lengths tend to decrease. In contrast, wet spells tend to exhibit constant lengths over the course of the season (44 out of 78 stations). The seasonal trend for storms indicates that the number and duration of storms tend to decrease in September; however, the storm depths tend to be more intense, particularly over the western portion of the domain. Overall, 90% of the area-averaged variance for dry-spell lengths can be explained by the random daily evolution of the stochastic model alone. For wet-spell lengths, the area-averaged variance explained by the stochastic models is 98% and for storm amounts it is 92%. These results suggest that the characteristics of most intraseasonal events over this region (i.e., spell lengths and storm amounts) can be captured by the random evolution of daily rainfall models, even with constant year-to-year statistical parameters, indicating that systematic variations in the background climatic conditions from one year to the next may contribute little to the characteristics of these events.


2009 ◽  
Vol 10 (5) ◽  
pp. 1218-1230 ◽  
Author(s):  
Bruce T. Anderson ◽  
Jingyun Wang ◽  
Suchi Gopal ◽  
Guido Salvucci

Abstract The regional variability in the summertime precipitation over the southwestern United States is studied using stochastic chain-dependent models generated from 70 yr of station-based daily precipitation observations. To begin, the spatiotemporal structure of the summertime seasonal mean precipitation over the southwestern United States is analyzed using two independent spatial cluster techniques. Four optimal clusters are identified, and their structures are robust across the techniques used. Next, regional chain-dependent models—comprising a previously dependent occurrence chain, an empirical rainfall coverage distribution, and an empirical rainfall amount distribution—are constructed over each subregime and are integrated to simulate the regional daily precipitation evolution across the summer season. Results indicate that generally less than 50% of the observed interannual variance of seasonal precipitation in a given region lies outside the regional chain-dependent models’ stochastic envelope of variability; this observed variance, which is not captured by the stochastic model, is sometimes referred to as the “potentially predictable” variance. In addition, only a small fraction of observed years (between 10% and 20% over a given subregime) contain seasonal mean precipitation anomalies that contribute to this potentially predictable variance. Further results indicate that year-to-year variations in daily rainfall coverage are the largest contributors to potentially predictable seasonal mean rainfall anomalies in most regions, whereas variations in daily rainfall frequency contribute the least. A brief analysis for one region highlights how the identification of years with potentially predictable precipitation characteristics can be used to better understand large-scale circulation patterns that modulate the underlying daily rainfall processes responsible for year-to-year variations in regional rainfall.


2009 ◽  
Vol 22 (22) ◽  
pp. 5918-5932 ◽  
Author(s):  
Jeremy L. Weiss ◽  
Christopher L. Castro ◽  
Jonathan T. Overpeck

Abstract Higher temperatures increase the moisture-holding capacity of the atmosphere and can lead to greater atmospheric demand for evapotranspiration, especially during warmer seasons of the year. Increases in precipitation or atmospheric humidity ameliorate this enhanced demand, whereas decreases exacerbate it. In the southwestern United States (Southwest), this means the greatest changes in evapotranspirational demand resulting from higher temperatures could occur during the hot–dry foresummer and hot–wet monsoon. Here seasonal differences in surface climate observations are examined to determine how temperature and moisture conditions affected evapotranspirational demand during the pronounced Southwest droughts of the 1950s and 2000s, the latter likely influenced by warmer temperatures now attributed mostly to the buildup of greenhouse gases. In the hot–dry foresummer during the 2000s drought, much of the Southwest experienced significantly warmer temperatures that largely drove greater evapotranspirational demand. Lower atmospheric humidity at this time of year over parts of the region also allowed evapotranspirational demand to increase. Significantly warmer temperatures in the hot–wet monsoon during the more recent drought also primarily drove greater evapotranspirational demand, but only for parts of the region outside of the core North American monsoon area. Had atmospheric humidity during the more recent drought been as low as during the 1950s drought in the core North American monsoon area at this time of year, greater evapotranspirational demand during the 2000s drought could have been more spatially extensive. With projections of future climate indicating continued warming in the region, evapotranspirational demand during the hot–dry and hot–wet seasons possibly will be more severe in future droughts and result in more extreme conditions in the Southwest, a disproportionate amount negatively impacting society.


2017 ◽  
Vol 44 (9) ◽  
pp. 4304-4312 ◽  
Author(s):  
Daniel Q. Tong ◽  
Julian X. L. Wang ◽  
Thomas E. Gill ◽  
Hang Lei ◽  
Binyu Wang

Author(s):  
Enrico Zorzetto ◽  
Laifang Li

AbstractBy modulating the moisture flux from ocean to adjacent land, the North Atlantic Subtropical High (NASH) western ridge significantly influences summer-season total precipitation over the Conterminous United States (CONUS). However, its influence on the frequency and intensity of daily rainfall events over the CONUS remains unclear. Here we introduce a Bayesian statistical model to investigate the impacts of the NASH western ridge position on key statistics of daily-scale summer precipitation, including the intensity of rainfall events, the probability of precipitation occurrence, and the probability of extreme values. These statistical quantities play a key role in characterizing both the impact of wet extremes (e.g., the probability of floods) and dry extremes. By applying this model to historical rain gauge records (1948-2019) covering the entire CONUS, we find that the western ridge of the NASH influences the frequency of rainfall as well as the distribution of rainfall intensities over extended areas of the CONUS. In particular, we find that the NASH ridge also modulates the frequency of extreme rainfall, especially that over part of the Southeast and upper Midwest. Our analysis underlines the importance of including the NASH western ridge position as a predictor for key statistical rainfall properties to be used for hydrological applications. This result is especially relevant for projecting future changes in daily rainfall regimes over the CONUS based on the predicted strengthening of the NASH in a warming climate.


2006 ◽  
Vol 7 (4) ◽  
pp. 739-754 ◽  
Author(s):  
Jingyun Wang ◽  
Bruce T. Anderson ◽  
Guido D. Salvucci

Abstract The interannual variability of summertime daily precipitation at 78 stations in the southwestern United States is studied using chain-dependent models and nonparametric empirical distributions of daily rainfall amounts. Modeling results suggest that a second-order chain-dependent model can optimally portray the temporal structure of the summertime daily precipitation process over the southwestern United States. The unconditioned second-order chain-dependent model, in turn, can explain approximately 75% of the interannual variance in the seasonal total wet days over the region and 83% of the interannual variance in the seasonal total precipitation. In addition, only a small fraction (generally smaller than 20%) of the observed years at any given station show statistically significant changes in the occurrence and intensity characteristics, related to either the number of seasonal total wet days or the distributions of daily rainfall amounts. Investigations of the year-to-year variations in the occurrence and intensity characteristics indicate that both variations are random (on interannual time scales), and they display similar significance in explaining the remaining 17% of interannual variance of seasonal total precipitation over the region. However, numerical tests suggest that the interannual variations of the two are not independent for the summertime monsoon precipitation, and that complex covariability that cannot be described with simple stochastic statistical models may exist between them.


2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.


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