Long-term Precipitation Trends

2021 ◽  
pp. 513-523
Author(s):  
R. G. Barry
Keyword(s):  
2013 ◽  
Vol 26 (12) ◽  
pp. 4168-4185 ◽  
Author(s):  
Sanjiv Kumar ◽  
Venkatesh Merwade ◽  
James L. Kinter ◽  
Dev Niyogi

Abstract The authors have analyzed twentieth-century temperature and precipitation trends and long-term persistence from 19 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). This study is focused on continental areas (60°S–60°N) during 1930–2004 to ensure higher reliability in the observations. A nonparametric trend detection method is employed, and long-term persistence is quantified using the Hurst coefficient, taken from the hydrology literature. The authors found that the multimodel ensemble–mean global land–average temperature trend (0.07°C decade−1) captures the corresponding observed trend well (0.08°C decade−1). Globally, precipitation trends are distributed (spatially) at about zero in both the models and in the observations. There are large uncertainties in the simulation of regional-/local-scale temperature and precipitation trends. The models’ relative performances are different for temperature and precipitation trends. The models capture the long-term persistence in temperature reasonably well. The areal coverage of observed long-term persistence in precipitation is 60% less (32% of land area) than that of temperature (78%). The models have limited capability to capture the long-term persistence in precipitation. Most climate models underestimate the spatial variability in temperature trends. The multimodel ensemble–average trend generally provides a conservative estimate of local/regional trends. The results of this study are generally not biased by the choice of observation datasets used, including Climatic Research Unit Time Series 3.1; temperature data from Hadley Centre/Climatic Research Unit, version 4; and precipitation data from Global Historical Climatology Network, version 2.


2010 ◽  
Vol 49 (8) ◽  
pp. 1597-1603 ◽  
Author(s):  
Robert J. Warren ◽  
Mark A. Bradford

Abstract The North Atlantic Oscillation (NAO) is a large-scale climate teleconnection that coincides with worldwide changes in weather. Its impacts have been documented at large scales, particularly in Europe, but not as much at regional scales. Furthermore, despite documented impacts on ecological dynamics in Europe, the NAO’s influence on North American biota has been somewhat overlooked. This paper examines long-term temperature and precipitation trends in the southern Appalachian Mountain region—a region well known for its biotic diversity, particularly in salamander species—and examines the connections between these trends and NAO cycles. To connect the NAO phase shifts with southern Appalachian ecology, trends in stream salamander abundance are also examined as a function of the NAO index. The results reported here indicate no substantial long-term warming or precipitation trends in the southern Appalachians and suggest a strong relationship between cool season (November–April) temperature and precipitation and the NAO. More importantly, trends in stream salamander abundance are best explained by variation in the NAO as salamanders are most plentiful during the warmer, wetter phases.


2008 ◽  
Vol 21 (8) ◽  
pp. 1807-1828 ◽  
Author(s):  
Jennifer C. Adam ◽  
Dennis P. Lettenmaier

Abstract River runoff to the Arctic Ocean has increased over the last century, primarily during the winter and spring and primarily from the major Eurasian rivers. Some recent studies have suggested that the additional runoff is due to increased northward transport of atmospheric moisture (and associated increased precipitation), but other studies show inconsistencies in long-term runoff and precipitation trends, perhaps partly due to biases in the observational datasets. Through trend analysis of precipitation, temperature, and streamflow data, the authors investigate the extent to which Eurasian Arctic river discharge changes are attributable to precipitation and temperature changes as well as to reservoir construction and operation between the years of 1936 and 2000. Two new datasets are applied: a gridded precipitation product, in which the low-frequency variability is constrained to match that of long-term bias-corrected precipitation station data, and a reconstructed streamflow product, in which the effects of reservoirs have been minimized using a physically based reservoir model. It is found that reservoir operations have primarily affected streamflow seasonality, increasing winter discharge and decreasing summer discharge. To understand the influences of climate on streamflow changes, the authors hypothesize three cases that would cause precipitation trends to be inconsistent with streamflow trends: first, for the coldest basins in northeastern Siberia, streamflow should be sensitive to warming primarily as a result of the melting of excess ground ice, and for these basins positive streamflow trends may exceed precipitation trends in magnitude; second, evapotranspiration (ET) in the warmer regions of western Siberia and European Russia is sensitive to warming and increased precipitation, therefore observed precipitation trends may exceed streamflow trends; and third, streamflow from the central Siberian basins should respond to both effects. It is found that, in general, these hypotheses hold true. In the coldest basins, streamflow trends diverged from precipitation trends starting in the 1950s to 1960s, and this divergence accelerated thereafter. In the warmest basins, precipitation trends consistently exceeded streamflow trends, suggesting that increased precipitation contributed to increases in both ET and streamflow. In the central basins, permafrost degradation and ET effects appear to be contributing to long-term streamflow trends in varying degrees for each basin. The results herein suggest that the extent and state of the permafrost underlying a basin is a complicating factor in understanding long-term changes in Eurasian Arctic river discharge.


2020 ◽  
Author(s):  
Ralph Trancoso ◽  
Jozef Syktus

<p>Changing precipitation patterns due to climate change is a critical concern affecting society and the environment. Projected changes in global seasonal precipitation are largely heterogeneous in space, time, magnitude and direction. Therefore, reconciling projected future precipitation is pivotal for climate change science and adaptation and mitigation schemes.</p><p>This research contributes to disentangle future precipitation uncertainty globally by exploring long-term trends in projected seasonal precipitation of 33 CMIP5 and 16 CMIP6 models for the period 1980-2100. We first estimate trend slopes and significance in long-term future seasonal precipitation using the Sen-Slope and Mann-Kendall tests and constrain trends with at least 10% of cumulative changes over the 120-year period. Then, we assess convergence in the direction of trends across seasons. We highlight the world’s jurisdictions with consistent drying and wetting patterns as well as the seasonal dominance of precipitation trends.</p><p>A consistent drying pattern – where at least 78% of GCMs have decreasing precipitation trends – was observed in Central America, South and North Africa, South Europe, Southern USA and Southern South America. Unlike, a strong convergence in projected long-term wetness – where at least 78% of GCMs have increasing precipitation trends – was observed across most of Asia, Central Africa, Northern Europe, Canada, Northern US and South Brazil and surrounds.</p><p>Results show convergence in direction of seasonal precipitation trends revealing the world’s jurisdictions more likely to experience changes in future precipitation patterns. The approach is promisor to summarize trends in seasonal time-series from multiple GCMs and better constrain wetting and drying precipitation patterns. This study provides meaningful insights to inform water resource management and climate change adaptation globally.</p>


2014 ◽  
Vol 35 (2) ◽  
pp. 303-320 ◽  
Author(s):  
Sebastian H. Mernild ◽  
Edward Hanna ◽  
Joseph R. McConnell ◽  
Michael Sigl ◽  
Andrew P. Beckerman ◽  
...  

2014 ◽  
Vol 27 (5) ◽  
pp. 2125-2142 ◽  
Author(s):  
John T. Abatzoglou ◽  
David E. Rupp ◽  
Philip W. Mote

Abstract Observed changes in climate of the U.S. Pacific Northwest since the early twentieth century were examined using four different datasets. Annual mean temperature increased by approximately 0.6°–0.8°C from 1901 to 2012, with corroborating indicators including a lengthened freeze-free season, increased temperature of the coldest night of the year, and increased growing-season potential evapotranspiration. Seasonal temperature trends over shorter time scales (<50 yr) were variable. Despite increased warming rates in most seasons over the last half century, nonsignificant cooling was observed during spring from 1980 to 2012. Observations show a long-term increase in spring precipitation; however, decreased summer and autumn precipitation and increased potential evapotranspiration have resulted in larger climatic water deficits over the past four decades. A bootstrapped multiple linear regression model was used to better resolve the temporal heterogeneity of seasonal temperature and precipitation trends and to apportion trends to internal climate variability, solar variability, volcanic aerosols, and anthropogenic forcing. The El Niño–Southern Oscillation and the Pacific–North American pattern were the primary modulators of seasonal temperature trends on multidecadal time scales: solar and volcanic forcing were nonsignificant predictors and contributed weakly to observed trends. Anthropogenic forcing was a significant predictor of, and the leading contributor to, long-term warming; natural factors alone fail to explain the observed warming. Conversely, poor model skill for seasonal precipitation suggests that other factors need to be considered to understand the sources of seasonal precipitation trends.


2014 ◽  
Vol 27 (22) ◽  
pp. 8487-8500 ◽  
Author(s):  
Stuart Evans ◽  
Roger Marchand ◽  
Thomas Ackerman

Abstract An atmospheric classification for northwestern Australia is used to define periods of monsoon activity and investigate the interannual and intraseasonal variability of the Australian monsoon, as well as long-term precipitation trends at Darwin. The classification creates a time series of atmospheric states, which two correspond to the active monsoon and the monsoon break. Occurrence of these states is used to define onset, retreat, seasonal intensity, and individual active periods within seasons. The authors demonstrate the quality of their method by showing it consistently identifies extended periods of precipitation as part of the monsoon season and recreates well-known relationships between Australian monsoon onset, intensity, and ENSO. The authors also find that onset and seasonal intensity are significantly correlated with ENSO as early as July. Previous studies have investigated the role of the Madden–Julian oscillation (MJO) during the monsoon by studying the frequency and duration of active periods, but these studies disagree on whether the MJO creates a characteristic period or duration. The authors use their metrics of monsoon activity and the Wheeler–Hendon MJO index to examine the timing of active periods relative to the phase of the MJO. It is shown that active periods preferentially begin during MJO phases 3 and 4, as the convective anomaly approaches Darwin, and end during phases 7 and 8, as the anomaly departs Darwin. Finally, the causes of the multidecadal positive precipitation trend at Darwin over the last few decades are investigated. It is found that an increase in the number of days classified as active, rather than changes in the daily rainfall rate during active monsoon periods, is responsible.


2013 ◽  
Vol 14 (1) ◽  
pp. 383-386
Author(s):  
John R. Christy

Abstract Coats raises issues regarding the utility of the snowfall metric presented by Christy in “Searching for information in 133 years of California snowfall observations,” suggesting that variance issues need more attention and that alternative metrics would be more useful than snowfall. Although discussed by Christy, the variance question is further addressed here. Regarding other metrics, it is shown that they are either inconsistently measured for long-term analysis or are actually consistent with Christy’s findings. In addition, it is demonstrated that Tahoe City, discussed by Coats, is inappropriate for examining long-term precipitation trends because of inconsistent measuring practices through time. Christy’s results remain unchanged.


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