scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

scholarly journals The Influence of Large-Scale Climate Variability on Winter Maximum Daily Precipitation over North America

2010 ◽  
Vol 23 (11) ◽  
pp. 2902-2915 ◽  
Author(s):  
Xuebin Zhang ◽  
Jiafeng Wang ◽  
Francis W. Zwiers ◽  
Pavel Ya Groisman
Keyword(s):  
North America ◽  
Climate Variability ◽  
El Niño ◽  
Extreme Precipitation ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
Winter Season ◽  
The North

Abstract The generalized extreme value (GEV) distribution is fitted to winter season daily maximum precipitation over North America, with indices representing El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the North Atlantic Oscillation (NAO) as predictors. It was found that ENSO and PDO have spatially consistent and statistically significant influences on extreme precipitation, while the influence of NAO is regional and is not field significant. The spatial pattern of extreme precipitation response to large-scale climate variability is similar to that of total precipitation but somewhat weaker in terms of statistical significance. An El Niño condition or high phase of PDO corresponds to a substantially increased likelihood of extreme precipitation over a vast region of southern North America but a decreased likelihood of extreme precipitation in the north, especially in the Great Plains and Canadian prairies and the Great Lakes/Ohio River valley.

scholarly journals The Role of Natural Climate Variability in Recent Tropical Expansion

2017 ◽  
Vol 30 (16) ◽  
pp. 6329-6350 ◽  
Author(s):  
Robert J. Allen ◽  
Mahesh Kovilakam
Keyword(s):  
Climate Variability ◽  
Large Scale ◽  
Climate Models ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Forced Response ◽  
Natural Climate Variability ◽  
Sst Variability ◽  
Natural Climate

Observations show the tropical belt has widened over the past few decades, a phenomenon associated with poleward migration of subtropical dry zones and large-scale atmospheric circulation. Coupled climate models also simulate tropical belt widening, but less so than observed. Reasons for this discrepancy, and the mechanisms driving the expansion remain uncertain. Here, the role of unforced, natural climate variability—particularly natural sea surface temperature (SST) variability—in recent tropical widening is shown. Compared to coupled ocean–atmosphere models, atmosphere-only simulations driven by observed SSTs consistently lead to larger rates of tropical widening, especially in the Northern Hemisphere (NH), highlighting the importance of recent SST evolution. Assuming the ensemble mean SSTs from historical simulations accurately represent the externally forced response, the observed SSTs can be decomposed into a forced and an unforced component. Targeted simulations with the Community Atmosphere Model, version 5 (CAM5), show that natural SST variability accounts for nearly all of the widening associated with recent SST evolution. This is consistent with the similarity of the unforced SSTs to the observed SSTs, both of which resemble a cold El Niño–Southern Oscillation/Pacific decadal oscillation (ENSO/PDO)-like SST pattern, which is associated with a wider tropical belt. Moreover, CAM5 coupled simulations with observed central to eastern tropical Pacific SSTs yield more than double the rate of widening compared to analogous simulations without prescribed tropical Pacific SSTs and reproduce the magnitude of tropical widening in atmosphere-only simulations. The results suggest that the bulk of recent tropical widening, particularly in the NH, is due to unforced, natural SST variability, primarily related to recent ENSO/PDO variability.

scholarly journals Role of Natural Climate Variability in the Detection of Anthropogenic Climate Change Signal for Mean and Extreme Precipitation at Local and Regional Scales

2018 ◽  
Vol 31 (11) ◽  
pp. 4241-4263 ◽  
Author(s):  
Jean-Luc Martel ◽  
Alain Mailhot ◽  
François Brissette ◽  
Daniel Caya
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Extreme Precipitation ◽  
Local Scale ◽  
Anthropogenic Climate Change ◽  
Climate Change Signal ◽  
Total Precipitation ◽  
Natural Climate Variability ◽  
The World ◽  
Natural Climate

Abstract Climate change will impact both mean and extreme precipitation, having potentially significant consequences on water resources. The implementation of efficient adaptation measures must rely on the development of reliable projections of future precipitation and on the assessment of their related uncertainty. Natural climate variability is a key uncertainty component, which can result in apparent decadal trends that may be greater or lower than the long-term underlying anthropogenic climate change trend. The goal of the present study is to assess how natural climate variability affects the ability to detect the climate change signal for mean and extreme precipitation. Annual and seasonal total precipitation are used as indicators of the mean, whereas annual and seasonal maximum daily precipitation are used as indicators of extremes. This is done using the CanESM2 50-member and CESM1 40-member large ensembles of simulations over the 1950–2100 period. At the local scale, results indicate that natural climate variability will dominate the uncertainty for annual and seasonal extreme precipitation going up to the end of the century in many parts of the world. The climate change signal can, however, be reliably detected much earlier at the regional scale for extreme precipitation. In the case of annual and seasonal total precipitation, the climate change signal can be reliably detected at the local scale without resorting to a regional analysis. Nonetheless, natural climate variability can impede the detection of the anthropogenic climate change signal until the middle to late century in many parts of the world for mean and extreme precipitation.

scholarly journals Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements

2019 ◽  
Vol 32 (23) ◽  
pp. 8087-8109 ◽  
Author(s):  
Mark D. Risser ◽  
Christopher J. Paciorek ◽  
Travis A. O’Brien ◽  
Michael F. Wehner ◽  
William D. Collins
Keyword(s):  
Extreme Precipitation ◽  
Seasonal Changes ◽  
Signal To Noise Ratio ◽  
Statistical Technique ◽  
In Situ Measurements ◽  
Absolute Sense ◽  
Underlying Causes ◽  
Changes Over Time ◽  
Future Work

Abstract The gridding of daily accumulated precipitation—especially extremes—from ground-based station observations is problematic due to the fractal nature of precipitation, and therefore estimates of long period return values and their changes based on such gridded daily datasets are generally underestimated. In this paper, we characterize high-resolution changes in observed extreme precipitation from 1950 to 2017 for the contiguous United States (CONUS) based on in situ measurements only. Our analysis utilizes spatial statistical methods that allow us to derive gridded estimates that do not smooth extreme daily measurements and are consistent with statistics from the original station data while increasing the resulting signal-to-noise ratio. Furthermore, we use a robust statistical technique to identify significant pointwise changes in the climatology of extreme precipitation while carefully controlling the rate of false positives. We present and discuss seasonal changes in the statistics of extreme precipitation: the largest and most spatially coherent pointwise changes are in fall (SON), with approximately 33% of CONUS exhibiting significant changes (in an absolute sense). Other seasons display very few meaningful pointwise changes (in either a relative or absolute sense), illustrating the difficulty in detecting pointwise changes in extreme precipitation based on in situ measurements. While our main result involves seasonal changes, we also present and discuss annual changes in the statistics of extreme precipitation. In this paper we only seek to detect changes over time and leave attribution of the underlying causes of these changes for future work.

scholarly journals Recent natural variability in global warming weakened phenological mismatch and selection on seasonal timing in great tits ( Parus major )

2021 ◽  
Vol 288 (1963) ◽  
Author(s):  
Marcel E. Visser ◽  
Melanie Lindner ◽  
Phillip Gienapp ◽  
Matthew C. Long ◽  
Stephanie Jenouvrier
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Variability ◽  
Parus Major ◽  
Great Tit ◽  
Trophic Levels ◽  
Natural Climate Variability ◽  
Seasonal Timing ◽  
Phenological Mismatch ◽  
Natural Climate

Climate change has led to phenological shifts in many species, but with large variation in magnitude among species and trophic levels. The poster child example of the resulting phenological mismatches between the phenology of predators and their prey is the great tit ( Parus major ), where this mismatch led to directional selection for earlier seasonal breeding. Natural climate variability can obscure the impacts of climate change over certain periods, weakening phenological mismatching and selection. Here, we show that selection on seasonal timing indeed weakened significantly over the past two decades as increases in late spring temperatures have slowed down. Consequently, there has been no further advancement in the date of peak caterpillar food abundance, while great tit phenology has continued to advance, thereby weakening the phenological mismatch. We thus show that the relationships between temperature, phenologies of prey and predator, and selection on predator phenology are robust, also in times of a slowdown of warming. Using projected temperatures from a large ensemble of climate simulations that take natural climate variability into account, we show that prey phenology is again projected to advance faster than great tit phenology in the coming decades, and therefore that long-term global warming will intensify phenological mismatches.

scholarly journals In Memoriam: Keith R Briffa, 1952–2017

The Holocene ◽  
2018 ◽  
Vol 28 (10) ◽  
pp. 1549-1553
Author(s):  
Timothy J Osborn ◽  
Philip D Jones ◽  
Edward R Cook
Keyword(s):  
Climate Variability ◽  
Late Holocene ◽  
Historical Context ◽  
Northern Eurasia ◽  
Primary Research ◽  
Natural Climate Variability ◽  
Climatic Trends ◽  
In Memoriam ◽  
Ring Analysis ◽  
Natural Climate

Keith R Briffa was one of the most influential palaeoclimatologists of the last 30 years. His primary research interests lay in Late-Holocene climate change with a geographical emphasis on northern Eurasia. His greatest impact was in the field of dendroclimatology, a field that he helped to shape. His contributions have been seminal to the development of sound methods for tree-ring analysis and in their proper application to allow the interpretation of climate variability from tree rings. This led to the development of many important records that allow us to understand natural climate variability on timescales from years to millennia and to set recent climatic trends in their historical context.

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