A Review of South Pacific Tropical Cyclones: Impacts of Natural Climate Variability and Climate Change

2020 ◽  
pp. 251-273
Author(s):  
Savin S. Chand ◽  
Andrew Dowdy ◽  
Samuel Bell ◽  
Kevin Tory
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Tropical Cyclones ◽  
South Pacific ◽  
Natural Climate Variability ◽  
Natural Climate

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 Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments

2018 ◽  
Vol 19 (1) ◽  
pp. 27-46 ◽  
Author(s):  
Magali Troin ◽  
Richard Arsenault ◽  
Jean-Luc Martel ◽  
François Brissette
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Substantial Contribution ◽  
Climate Change Signal ◽  
Natural Climate Variability ◽  
Degree Day ◽  
Natural Climate

Abstract Projected climate change effects on hydrology are investigated for the 2041–60 horizon under the A2 emission scenarios using a multimodel approach over two snowmelt-dominated catchments in Canada. An ensemble of 105 members was obtained by combining seven snow models (SMs), five potential evapotranspiration (PET) methods, and three hydrological model (HM) structures. The study was performed using high-resolution simulations from the Canadian Regional Climate Model (CRCM–15 km) driven by two members of the third-generation Canadian Coupled Global Climate Model (CGCM3). This study aims to compare various combinations of SM–PET–HM in terms of their ability to simulate streamflows under the current climate and to evaluate how they affect the assessment of the climate change–induced hydrological impacts at the catchment scale. The variability of streamflow response caused by the use of different SMs (degree-day versus degree-day/energy balance), PET methods (temperature-based versus radiation-based methods), and HM structures is evaluated, as well as the uncertainty due to the natural climate variability (CRCM intermember variability). The hydroclimatic simulations cover 1961–90 in the present period and 2041–60 in the future period. The ensemble spread of the climate change signal on streamflow is large and varies with catchments. Using the variance decomposition on three hydrologic indicators, the HM structure was found to make the most substantial contribution to uncertainty, followed by the choice of the PET methods or natural climate variability, depending on the hydrologic indicator and the catchment. Snow models played a minor, almost negligible role in the assessment of the climate change impacts on streamflow for the study catchments.

Relative impacts of human-induced climate change and natural climate variability

Nature ◽  
10.1038/17789 ◽  
1999 ◽  
Vol 397 (6721) ◽  
pp. 688-691 ◽  
Author(s):  
Mike Hulme ◽  
Elaine M. Barrow ◽  
Nigel W. Arnell ◽  
Paula A. Harrison ◽  
Timothy C. Johns ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Natural Climate Variability ◽  
Natural Climate

scholarly journals Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events

2021 ◽  
Author(s):  
Michael Schirmer ◽  
Adam Winstral ◽  
Tobias Jonas ◽  
Paolo Burlando ◽  
Nadav Peleg
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Variability ◽  
Weather Generator ◽  
Climate Change Signal ◽  
Natural Climate Variability ◽  
Sources Of Uncertainty ◽  
Snow Water ◽  
Snow Model ◽  
Natural Climate

Abstract. Climate projection studies of future changes in snow conditions and resulting rain-on-snow (ROS) flood events are subject to large uncertainties. Typically, emission scenario uncertainties and climate model uncertainties are included. This is the first study on this topic to also include quantification of natural climate variability, which is the dominant uncertainty for precipitation at local scales with large implications for e.g. runoff projections. To quantify natural climate variability, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 × 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The climate change signal for snow water resources stands out as early as mid-century from the noise originating from the three sources of uncertainty investigated, namely uncertainty in emission scenarios, uncertainty in climate models, and natural climate variability. For ROS events, a climate change signal toward more frequent and intense events was found for an RCP 8.5 scenario at high elevations at the end of the century, consistently with other studies. However, for ROS events with a substantial contribution of snowmelt to runoff (>20 %), the climate change signal was largely masked by sources of uncertainty. Only those ROS events where snowmelt does not play an important role during the event will occur considerably more frequently in the future, while ROS events with substantial snowmelt contribution will mainly occur earlier in the year but not more frequently. There are two reasons for this: first, although it will rain more frequently in midwinter, the snowpack will typically still be too cold and dry and thus cannot contribute significantly to runoff; second, the very rapid decline in snowpack toward early summer, when conditions typically prevail for substantial contributions from snowmelt, will result in a large decrease in ROS events at that time of the year. Finally, natural climate variability is the primary source of uncertainty in projections of ROS metrics until the end of the century, contributing more than 70 % of the total uncertainty. These results imply that both the inclusion of natural climate variability and the use of a snow model, which includes a physically-based processes representation of water retention, are important for ROS projections at the local scale.

scholarly journals Impact of anthropogenic climate change on wildfire across western US forests

2016 ◽  
Vol 113 (42) ◽  
pp. 11770-11775 ◽  
Author(s):  
John T. Abatzoglou ◽  
A. Park Williams
Keyword(s):  
Climate Change ◽  
United States ◽  
Climate Variability ◽  
Forest Fire ◽  
Anthropogenic Climate Change ◽  
Natural Climate Variability ◽  
Western Us ◽  
Fire Activity ◽  
Fire Area ◽  
Natural Climate

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000–2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984–2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

scholarly journals Flood history of the Bavarian Alpine Foreland since the late Middle Ages in the context of internal and external climate forcing factors

2014 ◽  
Vol 11 (7) ◽  
pp. 7409-7440 ◽  
Author(s):  
O. Böhm ◽  
J. Jacobeit ◽  
R. Glaser ◽  
K.-F. Wetzel
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Variability ◽  
Little Ice Age ◽  
Ice Age ◽  
Natural Climate Variability ◽  
Long Time ◽  
History Of ◽  
Alpine Foreland ◽  
Natural Climate

Abstract. This paper describes the flood history of the Bavarian part of the Alpine Foreland of Germany and addresses different questions concerning climate variability and flood frequencies from the 13th century until today. Will recent climatic change modify the flood frequencies within the Bavarian Alpine Foreland or are the flood frequencies varying due to altering climatic conditions since historical times? In the context of recent discussions whether man-made climate change will modify the present state of flood frequencies, a look back into the past is essential to understand the occurrence of floods in general and of recent floods in particular. In order to understand climatic variability and changes in a comprehensive way, it is necessary to review long time series. A perceived increase of summer floods in eastern Germany and Bavaria since 1997 requires examination of long time series to estimate changes in flood frequencies in a proper way. In view of the annual distribution of flood events within the Alpine Foreland of Germany, summer floods prove to be most important. Based on written historical sources, the flood history of the Alpine Foreland of Germany can be reconstructed back to the 14th century. One major result is the occurrence of "flood-rich" and "flood-poor" episodes in nearly cyclical sequences. Flood-rich periods were recorded in the periods 1300–1335, 1370–1450, 1470–1525, 1555–1590, 1615–1665, 1730–1780, 1820–1870, and 1910–1955 as well as in a 9th period beginning in 1980. The flood-rich periods are characterized by longer flood durations. Most of the flood-rich and flood-poor periods (in particular the beginning and the end of them) can be connected to changes in natural climate variability. These include changing sunspot numbers (as a measure of solar activity), so-called Little Ice Age Type Events (LIATEs) as well as changes in the North Atlantic Oscillation (NAO). Climate signals from external forcing factors, which could be used to explain the changing flood frequencies in the Bavarian Alpine Foreland, end in 1930. Relationships within the climate system such as the correlation of flood frequencies with the NAO have changed during the transition from the post Little Ice Age period to the Modern Climate Optimum around 1930. Natural climate variability might have been outperformed by anthropogenic climate change.

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