scholarly journals The role of winter precipitation and temperature on northern Eurasian streamflow trends

2012 ◽  
Vol 117 (D5) ◽  
pp. n/a-n/a ◽  
Author(s):  
Tara J. Troy ◽  
Justin Sheffield ◽  
Eric F. Wood
2010 ◽  
Vol 138 (6) ◽  
pp. 2447-2468 ◽  
Author(s):  
Naresh Devineni ◽  
A. Sankarasubramanian

Abstract Recent research into seasonal climate prediction has focused on combining multiple atmospheric general circulation models (GCMs) to develop multimodel ensembles. A new approach to combining multiple GCMs is proposed by analyzing the skill levels of candidate models contingent on the relevant predictor(s) state. To demonstrate this approach, historical simulations of winter (December–February, DJF) precipitation and temperature from seven GCMs were combined by evaluating their skill—represented by mean square error (MSE)—over similar predictor (DJF Niño-3.4) conditions. The MSE estimates are converted into weights for each GCM for developing multimodel tercile probabilities. A total of six multimodel schemes are considered that include combinations based on pooling of ensembles as well as on the long-term skill of the models. To ensure the improved skill exhibited by the multimodel scheme is statistically significant, rigorous hypothesis tests were performed comparing the skill of multimodels with each individual model’s skill. The multimodel combination contingent on Niño-3.4 shows improved skill particularly for regions whose winter precipitation and temperature exhibit significant correlation with Niño-3.4. Analyses of these weights also show that the proposed multimodel combination methodology assigns higher weights for GCMs and lesser weights for climatology during El Niño and La Niña conditions. On the other hand, because of the limited skill of GCMs during neutral Niño-3.4 conditions, the methodology assigns higher weights for climatology resulting in improved skill from the multimodel combinations. Thus, analyzing GCMs’ skill contingent on the relevant predictor state provides an alternate approach for multimodel combinations such that years with limited skill could be replaced with climatology.


2002 ◽  
Vol 33 (5) ◽  
pp. 415-424 ◽  
Author(s):  
Cintia B. Uvo ◽  
Ronny Berndtsson

Climate variability and climate change are of great concern to economists and energy producers as well as environmentalists as both affect the precipitation and temperature in many regions of the world. Among those affected by climate variability is the Scandinavian Peninsula. Particularly, its winter precipitation and temperature are affected by the variations of the so-called North Atlantic Oscillation (NAO). The objective of this paper is to analyze the spatial distribution of the influence of NAO over Scandinavia. This analysis is a first step to establishing a predictive model, driven by a climatic indicator such as NAO, for the available water resources of different regions in Scandinavia. Such a tool would be valuable for predicting potential of hydropower production one or more seasons in advance.


2018 ◽  
Vol 54 (9) ◽  
pp. 5986-6004 ◽  
Author(s):  
V. B. P. Chagas ◽  
P. L. B. Chaffe
Keyword(s):  

2001 ◽  
Vol 31 (2) ◽  
pp. 322-332 ◽  
Author(s):  
Ze'ev Gedalof ◽  
Dan J Smith

In this paper we review the ecology and physiology of mountain hemlock (Tsuga mertensiana (Bong.) Carrière) in the context of a dendroclimatological analysis. To better understand the relationship between mountain hemlock growth and climate variability throughout its range we have analyzed chronologies from 10 coastal sites, located along a transect extending from northern California to southern Alaska. The chronologies exhibit significant large-scale cross-correlations, with two distinct growth regions implied: chronologies from the northern Cascades in California, to the Queen Charlotte Islands, British Columbia, are correlated with each other but are distinct from Alaskan chronologies. While intervals of coherent reduced growth along the entire transect occur episodically throughout the record, intervals of coherent enhanced growth are less common. Response function analyses indicate that summer temperature is the most influential factor limiting growth throughout the study region, while winter precipitation is an additional limiting factor south of Alaska. Warm summer temperatures are associated with enhanced growth in the current year but with reduced growth in the following year. This response is believed to be a reflection of the energy required to mature cones initiated in the preceding year. The association with winter precipitation may reflect the role of deep, persistent snowpacks in regulating the duration of the growing season.


2014 ◽  
Vol 20 (12) ◽  
pp. 3743-3755 ◽  
Author(s):  
Yongshuo H Fu ◽  
Shilong Piao ◽  
Hongfang Zhao ◽  
Su-Jong Jeong ◽  
Xuhui Wang ◽  
...  

2021 ◽  
Vol 121 (2) ◽  
pp. 64-77
Author(s):  
Robert W. Ritzi ◽  
Lauren M. Roberson ◽  
Michael Bottomley

Continental-scale studies of North America suggest that the El Niño Southern Oscillation (ENSO) can cause winters to be warmer, with less precipitation, during El Niño conditions and colder, with more precipitation, during La Niña conditions in the Midwest United States. Two sources of historical records of precipitation and temperature in southwest Ohio from 1896 to 2016 were analyzed. Three statistical methodologies were used to test the hypothesis that anomalies in winter temperature and precipitation occurred in relation to ENSO phases. Eighty percent of El Niño winters had below-average winter precipitation; the average anomaly was −5 cm. Precipitation decreased with increase in El Niño strength as measured by the Multivariate ENSO Index (MEI). These results were statistically significant beyond the 95% level. However, variation in MEI only accounted for 3% of the overall variability in winter precipitation. Many of the drier winters on record, including the extrema, occurred during neutral winters. During La Niña winters precipitation was not statistically significantly different from that in neutral winters. Winter temperature was not statistically significantly different during El Niño and La Niña winters within the century of record. The results were consistent between separate analyses of data from the 2 different sources.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lu Dong ◽  
L. Ruby Leung ◽  
Fengfei Song ◽  
Jian Lu

AbstractMarked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty. Here we find that internal variability contributes > 70% and > 50% of uncertainty in the CA precipitation changes and the El Niño-like warming, respectively, based on analysis of 318 climate simulations from several multi-model and large ensembles. The Interdecadal Pacific Oscillation plays a key role in each contribution and in connecting the two via the westerly jet extension. This unifying understanding of the role of internal variability in CA precipitation provides critical guidance for reducing and communicating uncertainty to inform adaptation planning.


Author(s):  
Soraia El Baz ◽  
Kholoud Kahime

As a result of increased frequency and intensity of heat waves, increased floods and droughts, change in climate will affect biological, physical, and chemical components of water through different paths thus enhancing the risk of waterborne diseases. Identifying the role of weather in waterborne infection is a priority public health research issue as climate change is predicted to increase the frequency of extreme precipitation and temperature events. This chapter provides evidence that precipitation and temperature can affect directly or indirectly water quality and consequently affect the health human. This chapter also highlights the complex relationship between precipitation or temperature and transmission of waterborne disease such as diarrheal disease, gastroenteritis, cryptosporidiosis, giardiasis, and cholera.


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