Low-frequency variability and CO2 transient climate change. Part 3. Intermonthly and interannual variability

1994 ◽  
Vol 10 (6-7) ◽  
pp. 277-303
Author(s):  
Gerald A Meehl ◽  
Matthew Wheeler ◽  
Warren M Washington
1993 ◽  
Vol 8 (3) ◽  
pp. 117-133 ◽  
Author(s):  
Gerald A Meehl ◽  
Warren M Washington ◽  
Thomas R Karl

2011 ◽  
Vol 24 (14) ◽  
pp. 3609-3623 ◽  
Author(s):  
Fiona Johnson ◽  
Seth Westra ◽  
Ashish Sharma ◽  
Andrew J. Pitman

Abstract Climate change impact studies for water resource applications, such as the development of projections of reservoir yields or the assessment of likely frequency and amplitude of drought under a future climate, require that the year-to-year persistence in a range of hydrological variables such as catchment average rainfall be properly represented. This persistence is often attributable to low-frequency variability in the global sea surface temperature (SST) field and other large-scale climate variables through a complex sequence of teleconnections. To evaluate the capacity of general circulation models (GCMs) to accurately represent this low-frequency variability, a set of wavelet-based skill measures has been developed to compare GCM performance in representing interannual variability with the observed global SST data, as well as to assess the extent to which this variability is imparted in precipitation and surface pressure anomaly fields. A validation of the derived skill measures is performed using GCM precipitation as an input in a reservoir storage context, with the accuracy of reservoir storage estimates shown to be improved by using GCM outputs that correctly represent the observed low-frequency variability. Significant differences in the performance of different GCMs is demonstrated, suggesting that judicious selection of models is required if the climate impact assessment is sensitive to low-frequency variability. The two GCMs that were found to exhibit the most appropriate representation of global low-frequency variability for individual variables assessed were the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ECHAM4 and L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4); when considering all three variables, the Max Planck Institute (MPI) ECHAM5 performed well. Importantly, models that represented interannual variability well for SST also performed well for the other two variables, while models that performed poorly for SST also had consistently low skill across the remaining variables.


2017 ◽  
Vol 30 (13) ◽  
pp. 4997-5019 ◽  
Author(s):  
Stephan Juricke ◽  
Tim N. Palmer ◽  
Laure Zanna

In global ocean models, the representation of small-scale, high-frequency processes considerably influences the large-scale oceanic circulation and its low-frequency variability. This study investigates the impact of stochastic perturbation schemes based on three different subgrid-scale parameterizations in multidecadal ocean-only simulations with the ocean model NEMO at 1° resolution. The three parameterizations are an enhanced vertical diffusion scheme for unstable stratification, the Gent–McWilliams (GM) scheme, and a turbulent kinetic energy mixing scheme, all commonly used in state-of-the-art ocean models. The focus here is on changes in interannual variability caused by the comparatively high-frequency stochastic perturbations with subseasonal decorrelation time scales. These perturbations lead to significant improvements in the representation of low-frequency variability in the ocean, with the stochastic GM scheme showing the strongest impact. Interannual variability of the Southern Ocean eddy and Eulerian streamfunctions is increased by an order of magnitude and by 20%, respectively. Interannual sea surface height variability is increased by about 20%–25% as well, especially in the Southern Ocean and in the Kuroshio region, consistent with a strong underestimation of interannual variability in the model when compared to reanalysis and altimetry observations. These results suggest that enhancing subgrid-scale variability in ocean models can improve model variability and potentially its response to forcing on much longer time scales, while also providing an estimate of model uncertainty.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Giulia Bonino ◽  
Emanuele Di Lorenzo ◽  
Simona Masina ◽  
Doroteaciro Iovino

AbstractClimate variability and climate change in Eastern Boundary Upwelling Systems (EBUS) affect global marine ecosystems services. We use passive tracers in a global ocean model hindcast at eddy-permitting resolution to diagnose EBUS low-frequency variability over 1958–2015 period. The results highlight the uniqueness of each EBUS in terms of drivers and climate variability. The wind forcing and the thermocline depth, which are potentially competitive or complementary upwelling drivers under climate change, control EBUS low-frequency variability with different contributions. Moreover, Atlantic and Pacific upwelling systems are independent. In the Pacific, the only coherent variability between California and Humboldt Systems is associated with El Niño Southern Oscillation. The remaining low-frequency variance is partially explained by the North and South Pacific expressions of the Meridional Modes. In the Atlantic, coherent variability between Canary and Benguela Systems is associated with upwelling trends, which are not dynamically linked and represent different processes. In the Canary, a negative upwelling trend is connected to the Atlantic Multi-decadal Oscillation, while in the Benguela, a positive upwelling trend is forced by a global sea level pressure trend, which is consistent with the climate response to anthropogenic forcing. The residual variability is forced by localized offshore high sea level pressure variability.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1494
Author(s):  
Bernardo Teufel ◽  
Laxmi Sushama

Fluvial flooding in Canada is often snowmelt-driven, thus occurs mostly in spring, and has caused billions of dollars in damage in the past decade alone. In a warmer climate, increasing rainfall and changing snowmelt rates could lead to significant shifts in flood-generating mechanisms. Here, projected changes to flood-generating mechanisms in terms of the relative contribution of snowmelt and rainfall are assessed across Canada, based on an ensemble of transient climate change simulations performed using a state-of-the-art regional climate model. Changes to flood-generating mechanisms are assessed for both a late 21st century, high warming (i.e., Representative Concentration Pathway 8.5) scenario, and in a 2 °C global warming context. Under 2 °C of global warming, the relative contribution of snowmelt and rainfall to streamflow peaks is projected to remain close to that of the current climate, despite slightly increased rainfall contribution. In contrast, a high warming scenario leads to widespread increases in rainfall contribution and the emergence of hotspots of change in currently snowmelt-dominated regions across Canada. In addition, several regions in southern Canada would be projected to become rainfall dominated. These contrasting projections highlight the importance of climate change mitigation, as remaining below the 2 °C global warming threshold can avoid large changes over most regions, implying a low likelihood that expensive flood adaptation measures would be necessary.


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