scholarly journals Robust Decadal Variations in ENSO Diversity, and its Impact on Future Scenarios

2021 ◽  
Author(s):  
Bastien Dieppois ◽  
Antonietta Capotondi ◽  
Benjamin Pohl ◽  
Kwok Chun ◽  
Paul-Arthur Monerie ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Large Fraction ◽  
Future Climate Change ◽  
Thermocline Depth ◽  
Climate Change Scenarios ◽  
Decadal Variations ◽  
Enso Diversity

Abstract El Niño-Southern Oscillation (ENSO) shows a large diversity of events, whose modulation by climate variability and change, and their representation in climate models, limit our ability to predict their impact on ecosystems and human livelihood. Here, we introduce a new framework to analysze probabilistic changes in event-location and -intensity, which overcomes existing limitations in studying ENSO diversity. We find robust decadal variations in event intensities and locations in century-long observational datasets, which are associated with perturbations in equatorial wind-stress and thermocline depth, as well as extra-tropical anomalies in the North and South Pacific. A large fraction of CMIP5 and CMIP6 models appear capable of simulating such decadal variability in ENSO diversity, and the associated large-scale patterns. Projections of ENSO diversity in future climate change scenarios strongly depend on the magnitude of decadal variations, and the ability of climate models to reproduce them realistically over the 21st century.

scholarly journals ENSO diversity shows robust decadal variations that must be captured for accurate future projections

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Bastien Dieppois ◽  
Antonietta Capotondi ◽  
Benjamin Pohl ◽  
Kwok Pan Chun ◽  
Paul-Arthur Monerie ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Future Climate Change ◽  
Thermocline Depth ◽  
Climate Change Scenarios ◽  
Future System ◽  
Decadal Variations ◽  
Enso Diversity

AbstractEl Niño-Southern Oscillation (ENSO) shows a large diversity of events that is modulated by climate variability and change. The representation of this diversity in climate models limits our ability to predict their impact on ecosystems and human livelihood. Here, we use multiple observational datasets to provide a probabilistic description of historical variations in event location and intensity, and to benchmark models, before examining future system trajectories. We find robust decadal variations in event intensities and locations in century-long observational datasets, which are associated with perturbations in equatorial wind-stress and thermocline depth, as well as extra-tropical anomalies in the North and South Pacific. Some climate models are capable of simulating such decadal variability in ENSO diversity, and the associated large-scale patterns. Projections of ENSO diversity in future climate change scenarios strongly depend on the magnitude of decadal variations, and the ability of climate models to reproduce them realistically over the 21st century.

scholarly journals Downscale of future climate change scenarios applied to Recife-PE

2020 ◽  
Vol 9 (6) ◽  
pp. 361
Author(s):  
Rafaela Lisboa Costa ◽  
Heliofábio Barros Gomes ◽  
Fabrício Daniel Dos Santos Silva ◽  
Rodrigo Lins Da Rocha Júnior
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Future ◽  
Maximum Temperatures

The objective of this work was to analyze and compare results from two generations of global climate models (GCMs) simulations for the city of Recife-PE: CMIP3 and CMIP5. Differences and similarities in historical and future climate simulations are presented for four GCMs using CMIP3 scenarios A1B and A2 and for seven CMIP5 scenarios RCP4.5 and RCP8.5. The scale reduction technique applied to GCMs scenarios is statistical downscaling, employing the same set of large-scale atmospheric variables as predictors for both sets of scenarios, differing only in the type of reanalysis data used to characterize surface variables precipitation, maximum and minimum temperatures. For CMIP3 scenarios the simulated historical climate is 1961-1990 and CMIP5 is 1979-2000, and the validation period is ten years, 1991-2000 for CMIP3 and 2001-2010 for CMIP5. However, for both the future period analyzed is 2021-2050 and 2051-2080. Validation metrics indicated superior results from the historical simulations of CMIP5 over those of CMIP3 for precipitation and minimum and similar temperatures for maximum temperatures. For the future, both CMIP3 and CMIP5 scenarios indicate reduced precipitation and increased temperatures. The potencial evapotranspiration was calculated, projected to increase in scenarios A1B and A2 of CMIP3 and with behavior similar to that observed historically in scenarios RCP4.5 and 8.5.

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

<p>Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.  Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late).  A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21<sup>st</sup> century.</p>

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

scholarly journals Reduced global warming from CMIP6 projections when weighting models by performance and independence

2020 ◽  
Vol 11 (4) ◽  
pp. 995-1012
Author(s):  
Lukas Brunner ◽  
Angeline G. Pendergrass ◽  
Flavio Lehner ◽  
Anna L. Merrifield ◽  
Ruth Lorenz ◽  
...  
Keyword(s):  
Climate Change ◽  
Retrospective Analysis ◽  
Climate Models ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Uncertainty Range ◽  
Future Warming ◽  
The Mean

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as the mean and likely range. Here, we use a model weighting approach, which accounts for the models' historical performance based on several diagnostics as well as model interdependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we use previous-generation CMIP5 models as pseudo-observations in the historical period. The performance of the distribution weighted in the abovementioned manner with respect to matching the pseudo-observations in the future is then evaluated, and we find a mean increase in skill of about 17 % compared with the unweighted distribution. In addition, we show that our independence metric correctly clusters models known to be similar based on a CMIP6 “family tree”, which enables the application of a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (the fifth generation of the European Centre for Medium-Range Weather Forecasts Retrospective Analysis – ERA5, and the Modern-Era Retrospective analysis for Research and Applications, version 2 – MERRA-2), to constrain CMIP6 projections under weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios (SSP refers to the Shared Socioeconomic Pathways). Our results show a reduction in the projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 ∘C, compared with 4.1 ∘C without weighting; the likely (66%) uncertainty range is 3.1 to 4.6 ∘C, which equates to a 13 % decrease in spread. For SSP1-2.6, the weighted end-of-century warming is 1 ∘C (0.7 to 1.4 ∘C), which results in a reduction of −0.1 ∘C in the mean and −24 % in the likely range compared with the unweighted case.

scholarly journals Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications

2018 ◽  
Vol 31 (8) ◽  
pp. 3249-3264 ◽  
Author(s):  
Michael P. Byrne ◽  
Tapio Schneider
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Coupled Models ◽  
Near Surface ◽  
Circulation Changes

AbstractThe regional climate response to radiative forcing is largely controlled by changes in the atmospheric circulation. It has been suggested that global climate sensitivity also depends on the circulation response, an effect called the “atmospheric dynamics feedback.” Using a technique to isolate the influence of changes in atmospheric circulation on top-of-the-atmosphere radiation, the authors calculate the atmospheric dynamics feedback in coupled climate models. Large-scale circulation changes contribute substantially to all-sky and cloud feedbacks in the tropics but are relatively less important at higher latitudes. Globally averaged, the atmospheric dynamics feedback is positive and amplifies the near-surface temperature response to climate change by an average of 8% in simulations with coupled models. A constraint related to the atmospheric mass budget results in the dynamics feedback being small on large scales relative to feedbacks associated with thermodynamic processes. Idealized-forcing simulations suggest that circulation changes at high latitudes are potentially more effective at influencing global temperature than circulation changes at low latitudes, and the implications for past and future climate change are discussed.

scholarly journals Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

2015 ◽  
Vol 12 (24) ◽  
pp. 7503-7518 ◽  
Author(s):  
M. G. De Kauwe ◽  
S.-X. Zhou ◽  
B. E. Medlyn ◽  
A. J. Pitman ◽  
Y.-P. Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Soil Water Potential ◽  
Abrupt Onset ◽  
Future Climate Change ◽  
Land Surface Models ◽  
Drought Sensitivity ◽  
Coupled Climate Models ◽  
Surface Models

Abstract. Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.

scholarly journals A Modal Rendition of ENSO Diversity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Rajib Chattopadhyay ◽  
Shivsai Ajit Dixit ◽  
B. N. Goswami
Keyword(s):  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Slow Manifold ◽  
Disaster Mitigation ◽  
Coupled Models ◽  
Decadal Modulation ◽  
Enso Diversity ◽  
Modal Description

Abstract The El Nino and Southern Oscillation (ENSO) ‘diversity’ has been considered as a major factor limiting its predictability, a critical need for disaster mitigation associated with the trademark climatic swings of the ENSO. Improving climate models for ENSO forecasts relies on deeper understanding of the ENSO diversity but currently at a nascent stage. Here, we show that the ENSO diversity thought previously as ‘complex,’ arises largely as varied contributions from three leading modes of the ENSO to a given event. The ENSO ‘slow manifold’ can be fully described by three leading predictable modes, a quasi-quadrennial mode (QQD), a quasi-biennial (QB) mode and a decadal modulation of the quasi-biennial (DQB). The modal description of ENSO provides a framework for understanding the predictability of and global teleconnections with the ENSO. We further demonstrate it to be a useful framework for understanding biases of climate models in simulating and predicting the ENSO. Therefore, skillful prediction of all shades of ENSO depends critically on the coupled models’ ability to simulate the three modes with fidelity, providing basis for optimism for future of ENSO forecasts.

Potential state shifts in terrestrial ecosystems related to changes in El Niño-Southern Oscillation dynamics

2020 ◽  
Author(s):  
Mateo Duque-Villegas ◽  
Juan Fernando Salazar ◽  
Angela Maria Rendón
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Extreme Values ◽  
Southern Oscillation ◽  
Climatic Variability ◽  
Terrestrial Ecosystems ◽  
Eastern Africa ◽  
State Transitions ◽  
Climate Change Scenarios ◽  
Earth’S Climate

<p>The El Niño-Southern Oscillation (ENSO) phenomenon is regarded as a policy-relevant tipping element of the Earth's climate system. It has a prominent planetary-scale influence on climatic variability and it is susceptible to anthropogenic forcing, which could alter irreversibly its dynamics. Changes in frequency and/or amplitude of ENSO would have major implications for terrestrial hydrology and ecosystems. The amount of extreme events such as droughts and floods could vary regionally, as well as their intensities. Here, we use an intermediate complexity climate model, namely the Planet Simulator (PlaSim), to study the potential impact on Earth's climate and its terrestrial ecosystems of changing ENSO dynamics in a couple of experiments. Initially we investigate the global effects of a permanent El Niño, and then we analyse changes in the amplitude of the fluctuation. We found that PlaSim model yields a sensible representation of current large-scale climatological patterns, including ENSO-related variability, as well as realistic estimates of global energy and water budgets. For the permanent El Niño state, there were significant differences in the global distribution of water and energy fluxes that led to asymmetrical effects on vegetation production, which increased in the tropics and decreased in temperate regions. In terrestrial ecosystems of regions such as western North America, the Amazon rainforest, south-eastern Africa and Australia, we found that these El Niño-induced changes could be associated with biome state transitions. Particularly for Australia, we found country-wide aridification as a result of sustained El Niño conditions, which is a potential state in which recent wildfires would be even more dramatic. When the amplitude of the ENSO fluctuation changes, we found that although mean climatological values do not change significantly, extreme values of variables such as temperature and precipitation become more extreme. Our approach aims at recognizing potential threats for terrestrial ecosystems in climate change scenarios in which there are more frequent El Niño phenomena or the intensities of the ENSO phases change. Although it is not enough to prove such effects will be observed, we show a consistent picture and it should raise awareness about conservation of global ecosystems.</p>

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