Characterization of Simulated Extreme EL NIÑO Events and Projected Impacts on South American Climate Extremes by a Set of Cmip5 Global Climate Models

2021 ◽  
Author(s):  
Carla Gulizia ◽  
Martín N. Pirotte
Keyword(s):  
Climate Models ◽  
El Nino ◽  
Global Climate ◽  
Climate Extremes ◽  
Global Climate Models ◽  
South American ◽  
El Niño Events ◽  
South American Climate ◽  
Extreme El Niño

scholarly journals Effects of Excessive Equatorial Cold Tongue Bias on the Projections of Tropical Pacific Climate Change. Part II: The Extreme El Niño Frequency in CMIP5 Multi-Model Ensemble

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 851
Author(s):  
Gen Li ◽  
Zhiyuan Zhang ◽  
Bo Lu
Keyword(s):  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Equatorial Pacific ◽  
Western Pacific ◽  
Warming Pattern ◽  
El Niño Events ◽  
Rcp 8.5 ◽  
Extreme El Niño ◽  
El Nino Events

Under increased greenhouse gas (GHG) forcing, climate models tend to project a warmer sea surface temperature in the eastern equatorial Pacific than in the western equatorial Pacific. This El Niño-like warming pattern may induce an increase in the projected occurrence frequency of extreme El Niño events. The current models, however, commonly suffer from an excessive westward extension of the equatorial Pacific cold tongue accompanied by insufficient equatorial western Pacific precipitation. By comparing the Representative Concentration Pathway (RCP) 8.5 experiments with the historical simulations based on the Coupled Model Intercomparison Project phase 5 (CMIP5), a “present–future” relationship among climate models was identified: models with insufficient equatorial western Pacific precipitation error would have a weaker mean El Niño-like warming pattern as well as a lower increase in the frequency of extreme El Niño events under increased GHG forcing. Using this “present–future” relationship and the observed precipitation in the equatorial western Pacific, this study calibrated the climate projections in the tropical Pacific. The corrected projections showed a stronger El Niño-like pattern of mean changes in the future, consistent with our previous study. In particular, the projected increased occurrence of extreme El Niño events under RCP 8.5 forcing are underestimated by 30–35% in the CMIP5 multi-model ensemble before the corrections. This implies an increased risk of the El Niño-related weather and climate disasters in the future.

scholarly journals Projecting Rainfall Changes over the South American Altiplano

2011 ◽  
Vol 24 (17) ◽  
pp. 4577-4583 ◽  
Author(s):  
Marie Minvielle ◽  
René D. Garreaud
Keyword(s):  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Global Climate ◽  
Strong Dependence ◽  
Zonal Flow ◽  
Central Andes ◽  
High Elevation ◽  
Global Climate Models ◽  
South American ◽  
Westerly Flow

Consistent with its high elevation (>4000 m) and subtropical location (15°–25°S), the central Andes are expected to become warmer during the twenty-first century, affecting the population, ecosystems, and glaciers on the so-called South American Altiplano. Future changes in regional precipitation (even its sign) have been more difficult to estimate, partly because of the low resolution of current global climate models (GCMs) relative to the cross-mountain scale of the Andes. Nevertheless, summer season rainfall over the Altiplano exhibits a strong dependence on the magnitude of the zonal flow in the free troposphere, as quantified in this work using station data. Since GCMs indicate a consistent increase in westerly flow over the central Andes, hindering moisture transport from the interior of the continent, a simple regression analysis suggests a significant reduction (10%–30%) in Altiplano precipitation by the end of this century under moderate-to-strong greenhouse gas emission scenarios.

Capacity of climate models to capture multi-decadal hydrological variations over France

2020 ◽  
Author(s):  
Julien Boé ◽  
Rémy Bonnet
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Signal ◽  
River Flows ◽  
Climate Reconstructions ◽  
Decadal Variations ◽  
Instrumental Period

<p>In France, large multi-decadal variations in river flows have occurred over the instrumental period. These multi-decadal variations, likely of internal origin, could be a major source of uncertainties in the evolution of river flows during the 21st century, and especially during the coming decades, when the climate change signal is weaker. Depending on their phase, these variations might indeed strongly temporarily amplify or weaken (and even possibly reverse) the signal of climate change. From an adaptation perspective, it is crucial that hydrological projections correctly capture the amplitude of these multi-decadal variations, so that the associated uncertainties can be correctly estimated. The realism of hydrological projections in this context lies to a large extent in the realism of climate models, used at the first stage of the vast majority of the studies of the impacts of climate change.</p><p>The brevity of the instrumental record makes it difficult to characterize robustly multi-decadal hydro-climate variations, and the lack of observations for important hydrological variables makes it difficult to understand the mechanisms at play. The evaluation of climate models in this context is therefore also particularly challenging. </p><p>In this presentation, I will describe our work to better characterize hydrological variations over France in terms of amplitude and mechanisms, thanks to joint use of newly developed hydrological reconstructions beginning in the mid-nineteenth century, long observations from data-rescue efforts and paleo-climate reconstructions. Based on this work, I will then describe the results of the evaluation of multi-decadal hydrological variations in current global climate models, in terms of amplitude and associated mechanisms, taking into account the very large sampling uncertainties associated with the characterization of multi-decadal variations on relatively short periods. </p>

scholarly journals Possible Increased Frequency of ENSO-Related Dry and Wet Conditions over Some Major Watersheds in a Warming Climate

2020 ◽  
Vol 101 (4) ◽  
pp. E409-E426 ◽  
Author(s):  
Qiaohong Sun ◽  
Chiyuan Miao ◽  
Amir AghaKouchak ◽  
Iman Mallakpour ◽  
Duoying Ji ◽  
...  
Keyword(s):  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
River Basins ◽  
Global Climate Models ◽  
La Niña ◽  
Precipitation Pattern ◽  
La Nina

Abstract Predicting the changes in teleconnection patterns and related hydroclimate extremes can provide vital information necessary to adapt to the effects of the El Niño–Southern Oscillation (ENSO). This study uses the outputs of global climate models to assess the changes in ENSO-related dry/wet patterns and the frequency of severe dry/wet events. The results show anomalous precipitation responding asymmetrically to La Niña and El Niño, indicating the teleconnections may not simply be strengthened. A “dry to drier, wet to wetter” annual anomalous precipitation pattern was projected during La Niña phases in some regions, with drier conditions over southern North America, southern South America, and southern central Asia, and wetter conditions in Southeast Asia and Australia. These results are robust, with agreement from the 26 models and from a subset of 8 models selected for their good performance in capturing observed patterns. However, we did not observe a similar strengthening of anomalous precipitation during future El Niño phases, for which the uncertainties in the projected influences are large. Under the RCP4.5 emissions scenario, 45 river basins under El Niño conditions and 39 river basins under La Niña conditions were predicted to experience an increase in the frequency of severe dry events; similarly, 59 river basins under El Niño conditions and 61 river basins under La Niña conditions were predicted to have an increase in the frequency of severe wet events, suggesting a likely increase in the risk of floods. Our results highlight the implications of changes in ENSO patterns for natural hazards, disaster management, and engineering infrastructure.

scholarly journals Improvement of ENSO Simulation Based on Intermodel Diversity

2015 ◽  
Vol 28 (3) ◽  
pp. 998-1015 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Jong-Seong Kug
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Simulation ◽  
Central Pacific

Abstract In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupled global climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the close connection between the interannual variability and climatological states, the distinctive relation between the intermodel diversity of the interannual variability and that of the basic state is found. Based on this relation, the simulated interannual variabilities can be improved, by correcting their climatological bias. To test this methodology, the dominant intermodel difference in precipitation responses during El Niño–Southern Oscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominant intermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominant intermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatology than the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positive ENSO precipitation anomalies to the east (west). Based on the model’s systematic errors in atmospheric ENSO response and bias, the models with better climatological state tend to simulate more realistic atmospheric ENSO responses. Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. After the statistical correction, simulating quality of the MME ENSO precipitation is distinctively improved. These results provide a possibility that the present methodology can be also applied to improving climate projection and seasonal climate prediction.

scholarly journals Climate Change Impact Assessment for Aji Basin Using Statistical Downscaling and Bias Correction of Climate Model Outputs

2016 ◽  
Vol 11 (2) ◽  
pp. 670-678 ◽  
Author(s):  
N. S Vithlani ◽  
H. D Rank
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Climate Extremes ◽  
Global Climate Models ◽  
Climate Indices ◽  
Climate Projections

For the future projections Global climate models (GCMs) enable development of climate projections and relate greenhouse gas forcing to future potential climate states. When focusing it on smaller scales it exhibit some limitations to overcome this problem, regional climate models (RCMs) and other downscaling methods have been developed. To ensure statistics of the downscaled output matched the corresponding statistics of the observed data, bias correction was used. Quantify future changes of climate extremes were analyzed, based on these downscaled data from two RCMs grid points. Subset of indices and models, results of bias corrected model output and raw for the present day climate were compared with observation, which demonstrated that bias correction is important for RCM outputs. Bias correction directed agreements of extreme climate indices for future climate it does not correct for lag inverse autocorrelation and fraction of wet and dry days. But, it was observed that adjusting both the biases in the mean and variability, relatively simple non-linear correction, leads to better reproduction of observed extreme daily and multi-daily precipitation amounts. Due to climate change temperature and precipitation will increased day by day.

scholarly journals How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

2014 ◽  
Vol 27 (15) ◽  
pp. 5673-5692 ◽  
Author(s):  
Hui Wang ◽  
Lindsey Long ◽  
Arun Kumar ◽  
Wanqiu Wang ◽  
Jae-Kyung E. Schemm ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Global Climate ◽  
Global Climate Models ◽  
Track Density ◽  
Cp El Niño ◽  
Ep El Niño ◽  
The U.S

Abstract The variability of Atlantic tropical cyclones (TCs) associated with El Niño–Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions during eastern Pacific (EP) and central Pacific (CP) El Niño events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Niño and stronger activity during La Niña. For CP El Niño, there is a slight increase in the number of TCs as compared with EP El Niño. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region during CP El Niño as in observations. The difference between the models and observations is likely due to the bias of the models in response to the shift of tropical heating associated with CP El Niño, as well as the model bias in the mean circulation.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models
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