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 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.

Footprints of Tropical Cyclones in WNP Summer Monsoon Variability

2020 ◽  
Author(s):  
Huang-Hsiung Hsu
Keyword(s):  
Climate Variability ◽  
Tropical Cyclones ◽  
Large Scale ◽  
Climate Models ◽  
Southern Oscillation ◽  
Intraseasonal Oscillation ◽  
Low Frequency ◽  
Monsoon Trough ◽  
Teleconnection Pattern ◽  
Large Scale Circulation

<p>Tropical cyclones (TCs) in the western North Pacific (WNP) are modulated by large-scale circulation systems such monsoon trough, intraseasonal oscillation, teleconnection pattern, El Niño and Southern Oscillation, and some interdecadal oscillations. While the low-frequency, large-scale circulation produces a clustering effect on TCs, the latter in return leave marked footprints in climate mean state and variability because of large amplitudes in circulation and strong heating. In this study, we applied PV inversion technique to remove TCs from reanalysis and evaluate their contribution to mean circulation and climate variability. It is found that the mean climatological circulation (e.g., low-level monsoon trough and upper-tropospheric anticyclone) would be much weaker with TCs removed. Intraseasonal and interannual variance of certain variables could decrease by as much as 40–50 percent. An accompanied study indicated that TCs had slowed down the sea surface warming in the WNP for the past few decades because of TC-induced cooling. Our results suggest that TC effect has to be considered to understand the climate variability in the tropical atmosphere and ocean. The ensemble effect of TCs, at least in the statistical sense, has to be resolved in climate models to better simulate climate variability and produce more reliable climate projection in the TC-prone regions.</p>

scholarly journals Impacts of bias nonstationarity of climate model outputs on hydrological simulations

2020 ◽  
Vol 51 (5) ◽  
pp. 925-941
Author(s):  
Yu Hui ◽  
Yuni Xu ◽  
Jie Chen ◽  
Chong-Yu Xu ◽  
Hua Chen
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Time Windows ◽  
Natural Climate Variability ◽  
Change Impact ◽  
Natural Climate ◽  
Precipitation And Temperature

Abstract Bias correction methods are based on the assumption of bias stationarity of climate model outputs. However, this assumption may not be valid, because of the natural climate variability. This study investigates the impacts of bias nonstationarity of climate models simulated precipitation and temperature on hydrological climate change impact studies. The bias nonstationarity is determined as the range of difference in bias over multiple historical periods with no anthropogenic climate change for four different time windows. The role of bias nonstationarity in future climate change is assessed using the signal-to-noise ratio as a criterion. The results show that biases of climate models simulated monthly and annual precipitation and temperature vary with time, especially for short time windows. The bias nonstationarity of precipitation plays a great role in future precipitation change, while the role of temperature bias is not important. The bias nonstationarity of climate model outputs is amplified when driving a hydrological model for hydrological simulations. The increase in the length of time window can mitigate the impacts of bias nonstationarity for streamflow projections. Thus, a long time period is suggested to be used to calibrate a bias correction method for hydrological climate change impact studies to reduce the influence of natural climate variability.

scholarly journals Interannual Variability of Tropical Cyclones in the Australian Region: Role of Large-Scale Environment

2008 ◽  
Vol 21 (5) ◽  
pp. 1083-1103 ◽  
Author(s):  
Hamish A. Ramsay ◽  
Lance M. Leslie ◽  
Peter J. Lamb ◽  
Michael B. Richman ◽  
Mark Leplastrier
Keyword(s):  
Interannual Variability ◽  
Large Scale ◽  
Vertical Wind Shear ◽  
Principal Component ◽  
Relative Vorticity ◽  
Vertical Shear ◽  
Scale Parameters ◽  
Australian Region ◽  
Sst Variability

Abstract This study investigates the role of large-scale environmental factors, notably sea surface temperature (SST), low-level relative vorticity, and deep-tropospheric vertical wind shear, in the interannual variability of November–April tropical cyclone (TC) activity in the Australian region. Extensive correlation analyses were carried out between TC frequency and intensity and the aforementioned large-scale parameters, using TC data for 1970–2006 from the official Australian TC dataset. Large correlations were found between the seasonal number of TCs and SST in the Niño-3.4 and Niño-4 regions. These correlations were greatest (−0.73) during August–October, immediately preceding the Australian TC season. The correlations remain almost unchanged for the July–September period and therefore can be viewed as potential seasonal predictors of the forthcoming TC season. In contrast, only weak correlations (<+0.37) were found with the local SST in the region north of Australia where many TCs originate; these were reduced almost to zero when the ENSO component of the SST was removed by partial correlation analysis. The annual frequency of TCs was found to be strongly correlated with 850-hPa relative vorticity and vertical shear of the zonal wind over the main genesis areas of the Australian region. Furthermore, correlations between the Niño SST and these two atmospheric parameters exhibited a strong link between the Australian region and the Niño-3.4 SST. A principal component analysis of the SST dataset revealed two main modes of Pacific Ocean SST variability that match very closely with the basinwide patterns of correlations between SST and TC frequencies. Finally, it is shown that the correlations can be increased markedly (e.g., from −0.73 to −0.80 for the August–October period) by a weighted combination of SST time series from weakly correlated regions.

scholarly journals Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños

2021 ◽  
Author(s):  
Iñigo Gómara ◽  
Belén Rodríguez-Fonseca ◽  
Elsa Mohino ◽  
Teresa Losada ◽  
Irene Polo ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Marine Ecosystem ◽  
Ecosystem Model ◽  
Tropical Pacific ◽  
Equatorial Atlantic ◽  
Climate Conditions ◽  
Marine Food Web ◽  
Marine Ecosystem Model ◽  
The Tropical Pacific

AbstractTropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.

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.

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