scholarly journals Analyzing ENSO Teleconnections in CMIP Models as a Measure of Model Fidelity in Simulating Precipitation

2013 ◽  
Vol 26 (13) ◽  
pp. 4431-4446 ◽  
Author(s):  
Baird Langenbrunner ◽  
J. David Neelin

Abstract The accurate representation of precipitation is a recurring issue in climate models. El Niño–Southern Oscillation (ENSO) precipitation teleconnections provide a test bed for comparison of modeled to observed precipitation. The simulation quality for the atmospheric component of models in the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) is assessed here, using the ensemble of runs driven by observed sea surface temperatures (SSTs). Simulated seasonal precipitation teleconnection patterns are compared to observations during 1979–2005 and to the ensemble of CMIP phase 3 (CMIP3). Within regions of strong observed teleconnections (equatorial South America, the western equatorial Pacific, and a southern section of North America), there is little improvement in the CMIP5 ensemble relative to CMIP3 in amplitude and spatial correlation metrics of precipitation. Spatial patterns within each region exhibit substantial departures from observations, with spatial correlation coefficients typically less than 0.5. However, the atmospheric models do considerably better in other measures. First, the amplitude of the precipitation response (root-mean-square deviation over each region) is well estimated by the mean of the amplitudes from the individual models. This is in contrast with the amplitude of the multimodel ensemble mean, which is systematically smaller (by about 30%–40%) in the selected teleconnection regions. Second, high intermodel agreement on teleconnection sign provides a good predictor for high model agreement with observed teleconnections. The ability of the model ensemble to yield amplitude and sign measures that agree with the observed signal for ENSO precipitation teleconnections lends supporting evidence for the use of corresponding measures in global warming projections.

2007 ◽  
Vol 20 (7) ◽  
pp. 1265-1284 ◽  
Author(s):  
Qin Zhang ◽  
Arun Kumar ◽  
Yan Xue ◽  
Wanqiu Wang ◽  
Fei-Fei Jin

Abstract Simulations from the National Centers for Environmental Prediction (NCEP) coupled model are analyzed to document and understand the behavior of the evolution of the El Niño–Southern Oscillation (ENSO) cycle. The analysis is of importance for two reasons: 1) the coupled model used in this study is also used operationally to provide model-based forecast guidance on a seasonal time scale, and therefore, an understanding of the ENSO mechanism in this particular coupled system could also lead to an understanding of possible biases in SST predictions; and 2) multiple theories for ENSO evolution have been proposed, and coupled model simulations are a useful test bed for understanding the relative importance of different ENSO mechanisms. The analyses of coupled model simulations show that during the ENSO evolution the net surface heat flux acts as a damping mechanism for the mixed-layer temperature anomalies, and positive contribution from the advection terms to the ENSO evolution is dominated by the linear advective processes. The subsurface temperature–SST feedback, referred to as thermocline feedback in some theoretical literature, is found to be the primary positive feedback, whereas the advective feedback by anomalous zonal currents and the thermocline feedback are the primary sources responsible for the ENSO phase transition in the model simulation. The basic mechanisms for the model-simulated ENSO cycle are thus, to a large extent, consistent with those highlighted in the recharge oscillator. The atmospheric anticyclone (cyclone) over the western equatorial northern Pacific accompanied by a warm (cold) phase of the ENSO, as well as the oceanic Rossby waves outside of 15°S–15°N and the equatorial higher-order baroclinic modes, all appear to play minor roles in the model ENSO cycles.


2020 ◽  
Author(s):  
Stephanie Fiedler ◽  
Traute Crueger ◽  
Roberta D’Agostino ◽  
Karsten Peters ◽  
Tobias Becker ◽  
...  

<p>Climate models are known to have biases in tropical precipitation. We assessed to what extent simulations of tropical precipitation have improved in the new Coupled Model Intercomparison Project (CMIP) phase six, using state-of-the-art observational products and model results from the earlier CMIP phases three and five. We characterize tropical precipitation with different well-established metrics. Our assessment includes (1) general aspects of the mean climatology like precipitation associated with the Intertropical Convergence Zone and shallow cloud regimes in the tropics, (2) solar radiative effects including the summer monsoons and the time of occurrence of tropical precipitation in the course of the day, (3) modes of internal variability such as the Madden-Julian Oscillation and the El Niño Southern Oscillation, and (4) changes in the course of the 20th century. The results point to improvements of CMIP6 models for some metrics, e.g., the occurrence of drizzle events and consecutive dry days. However, no improvements of CMIP6 models are identified for other aspects of tropical precipitation. These include the area and intensity of the global summer monsoon as well as the diurnal cycle of the tropical precipitation amount, frequency and intensity.</p><p>All our metrics taken together, CMIP6 models show no systematic improvement of tropical precipitation across different temporal and spatial scales. The model biases in the spatial distribution of tropical precipitation are typically larger than the changes associated with anthropogenic warming. Given the pace of climate change as compared to the pace of climate model improvements, we suggest to use novel modeling approaches to understand the responseof tropical precipitation to changes in atmospheric composition.</p>


2015 ◽  
Vol 11 (4) ◽  
pp. 3853-3895 ◽  
Author(s):  
R. Batehup ◽  
S. McGregor ◽  
A. J. E. Gallant

Abstract. Reconstructions of the El Niño-Southern Oscillation (ENSO) ideally require high-quality, annually-resolved and long-running paleoclimate proxy records in the eastern tropical Pacific Ocean, located in ENSO's centre-of-action. However, to date, the paleoclimate records that have been extracted in the region are short or temporally and spatially sporadic, limiting the information that can be provided by these reconstructions. Consequently, most ENSO reconstructions exploit the downstream influences of ENSO on remote locations, known as teleconnections, where longer records from paleoclimate proxies exist. However, using teleconnections to reconstruct ENSO relies on the assumption that the relationship between ENSO and the remote location is stationary in time. Increasing evidence from observations and climate models suggests that some teleconnections are, in fact, non-stationary, potentially threatening the validity of those paleoclimate reconstructions that exploit teleconnections. This study examines the implications of non-stationary teleconnections on modern multi-proxy reconstructions of ENSO. The sensitivity of the reconstructions to non-stationary teleconnections were tested using a suite of idealized pseudoproxy experiments that employed output from a fully coupled global climate model. Reconstructions of the variance in the Niño 3.4 index, representing ENSO variability, were generated using four different methods to which surface temperature data from the GFDL CM2.1 was applied as a pseudoproxy. As well as sensitivity of the reconstruction to the method, the experiments tested the sensitivity of the reconstruction to the number of non-stationary pseudoproxies and the location of these proxies. ENSO reconstructions in the pseudoproxy experiments were not sensitive to non-stationary teleconnections when global, uniformly-spaced networks of a minimum of approximately 20 proxies were employed. Neglecting proxies from ENSO's center-of-action still produced skillful reconstructions, but the chance of generating a skillful reconstruction decreased. Reconstruction methods that utilized raw time series were the most sensitive to non-stationary teleconnections, while calculating the running variance of pseudoproxies first, appeared to improve the robustness of the resulting reconstructions. The results suggest that caution should be taken when developing reconstructions using proxies from a single teleconnected region, or those that use less than 20 source proxies.


2021 ◽  
Author(s):  
Abraham Torres-Alavez ◽  
Fred Kucharski ◽  
Erika Coppola ◽  
Lorena Castro

<p>Using high-spatial-resolution regional simulations from the global program, Coordinated Regional Climate Downscaling Experiment-Coordinated Output for Regional Evaluations (CORDEX-CORE), we examine the capability of regional climate models (RCMs) to represent the El Niño–Southern Oscillation (ENSO) precipitation and surface air temperature teleconnections during boreal winter (December-February). This study uses CORDEX-CORE simulations for the period 1975-2004 with two RCMs, the RegCM4 and REMO, driven by three General Circulation Models (GCMs) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5). The RCM simulations were run at a 25-km grid spacing over Africa, Central and North America, South Asia and South America.</p><p>The teleconnection patterns are calculated in the reanalysis data (observations), and these results are compared to those of the ensemble and individual simulations of both the GCM and RCM. Linear regression is used to calculate the teleconnection patterns and a permutation test is applied to calculate the statistical significance of the regression coefficients. Results show that overall, the ENSO signal from the GCMs is preserved in the ensemble and the individual RCM simulations over most of the regions analyzed. These reproduced most of the observed regional responses to ENSO forcing and showing teleconnection signals statistically significant at the 95% level. Furthermore, in some cases, the ensemble and individual simulations of RCMs improve the spatial pattern and the amplitude of the ENSO precipitation response of the GCMs, particularly over southern Africa, the Arabian-Asian region, and the region composed of Mexico and the southern United States. These results show the potential value of the GCM-RCM downscaling systems not only in the context of climate change research but also for seasonal to annual prediction.</p>


2020 ◽  
Author(s):  
Andréa S. Taschetto ◽  
Caroline C. Ummenhofer ◽  
Malte F. Stuecker ◽  
Dietmar Dommenget ◽  
Karumuri Ashok ◽  
...  

<p>The warming of the equatorial Pacific associated with the El Niño–Southern Oscillation (ENSO) causes profound impacts on rainfall and temperature in the tropics and extratropics. El Niño drives changes in the Walker and Hadley circulations, warms the tropics and affects the neighboring ocean basins, favoring a short-term rise in global temperatures. We will present an overview of the atmospheric teleconnections driven by ENSO and its diversity focusing on the impacts over land and remote ocean basins. During El Niño, dry conditions are generally observed in the Maritime Continent, northern South America, South Asia and South Africa, while wet weather typically occurs in southwestern North America, western Antarctica, and east Africa. Global effects during La Niña are overall the opposite to El Niño, however this assumption is not true for all regions. ENSO atmospheric teleconnections are non-linear in part due to different locations of the anomalous equatorial warming (Eastern versus Central Pacific events) superimposed on the Pacific mean state, as well as interactions with the annual cycle, off-equatorial regions, remote ocean basins, and other modes of climate variability. Adding to this complex behavior, ENSO teleconnections are non-stationary either due to deterministic low-frequency modulations or stochastic variability, the latter being a factor generally overlooked in the literature. As the world warms in response to greenhouse gas forcing, ENSO atmospheric teleconnections are expected to change, despite large uncertainties in ENSO projections. We will discuss the limitations of climate models in representing realistic teleconnections from the tropical Pacific to remote regions and some of the challenges for future projections.</p>


2020 ◽  
Author(s):  
Yuqiong Zheng

<p>This study evaluates the ability of 35 climate models, which participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical climate simulations, in reproducing the connection between boreal spring Arctic Oscillation (AO) and its following winter El Niño-Southern Oscillation (ENSO). The spring AO-winter ENSO correlations range from -0.41 to 0.44 among the 35 models for the period of 1958-2005. Ensemble means of the models with significant positive and negative AO-ENSO correlations both show strong spring sea surface temperature (SST) cooling in the subtropical North Pacific during a positive phase of spring AO, which is conducive to occurrence of a La Niña event in the following winter. However, the models with positive AO-ENSO relations produce a pronounced spring cyclonic anomaly over the subtropical northwestern Pacific and westerly anomalies over the tropical western Pacific (TWP). These westerly wind anomalies would lead to SST warming and positive precipitation anomalies in the tropical central-eastern Pacific (TCEP) during the following summer, which could maintain and develop into an El Niño-like pattern in the following winter via a positive air-sea feedback. By contrast, the models with negative AO-ENSO connections fail to reproduce the spring AO-related cyclonic anomaly over the subtropical northwestern Pacific and westerly wind anomalies in the TWP. Thus, these models would produce a La Niña-like pattern in the subsequent winter. Difference in the spring AO-associated atmospheric anomalies over the subtropical North Pacific among the CMIP5 models may be attributed to biases of the models in simulating the spring climatological storm track.</p>


2016 ◽  
Vol 29 (4) ◽  
pp. 1477-1496 ◽  
Author(s):  
Penelope Maher ◽  
Steven C. Sherwood

Abstract Expansion of the tropics will likely affect subtropical precipitation, but observed and modeled precipitation trends disagree with each other. Moreover, the dynamic processes at the tropical edge and their interactions with precipitation are not well understood. This study assesses the skill of climate models to reproduce observed Australian precipitation variability at the tropical edge. A multivariate linear independence approach distinguishes between direct (causal) and indirect (circumstantial) precipitation drivers that facilitate clearer attribution of model errors and skill. This approach is applied to observed precipitation and ERA-Interim reanalysis data and a representative subset of four models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and their CMIP3 counterparts. The drivers considered are El Niño–Southern Oscillation, southern annular mode, Indian Ocean dipole, blocking, and four tropical edge metrics (position and intensity of the subtropical ridge and subtropical jet). These models are skillful in representing the covariability of drivers and their influence on precipitation. However, skill scores have not improved in the CMIP5 subset relative to CMIP3 in either respect. The Australian precipitation response to a poleward-located Hadley cell edge remains uncertain, as opposing drying and moistening mechanisms complicate the net response. Higher skill in simulating driver covariability is not consistently mirrored by higher precipitation skill. This provides further evidence that modeled precipitation does not respond correctly to large-scale flow patterns; further improvements in parameterized moist physics are needed before the subtropical precipitation responses can be fully trusted. The multivariate linear independence approach could be applied more widely for practical model evaluation.


2015 ◽  
Vol 28 (3) ◽  
pp. 998-1015 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Jong-Seong Kug

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.


2021 ◽  
Vol 14 (2) ◽  
pp. 923-934
Author(s):  
Juan A. Añel ◽  
Michael García-Rodríguez ◽  
Javier Rodeiro

Abstract. Over the past few years, increasing attention has been focused on the need to publish computer code as an integral part of the research process. This has been reflected in improved policies on publication in scientific journals, including key related issues such as repositories and licensing. We explore the state of the art of code availability and the sharing of climate models using the Fifth Coupled Model Intercomparison Project (CMIP5) models as a test bed, and we include some particular reflections on this case. Our results show that there are many limitations in terms of access to the code for these climate models and that the climate modelling community needs to improve its code-sharing practice to comply with best practice in this regard and the most recent editorial publishing policies.


2020 ◽  
Author(s):  
Jonathan Beverley ◽  
Mat Collins ◽  
Hugo Lambert ◽  
Rob Chadwick

<p>El Niño–Southern Oscillation (ENSO) has major impacts on the weather and climate across many regions of the world. Understanding how these teleconnections may change in the future is therefore an important area of research. Here, we use simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to investigate future changes in ENSO teleconnections in the North Pacific/North America sector.</p><p>Precipitation over the equatorial Pacific associated with ENSO is projected to shift eastwards under global warming as a result of greater warming in the east Pacific, which reduces the barrier to convection as the warm pool expands eastwards. As a result, there is medium confidence (IPCC AR5 report) that ENSO teleconnections will shift eastwards in the North Pacific/North America sector. In the CMIP6 models, the present day teleconnection is relatively well simulated, with most models showing an anomalously deep Aleutian low and associated positive temperature anomalies over Alaska and northern North America in El Niño years. In the future warming simulations (we use abrupt-4xCO2, in which CO2 concentrations are immediately quadrupled from the global annual mean 1850 value), in agreement with the IPCC AR5 report, the North America teleconnection and associated circulation change is shifted eastwards in most models. However, it is also significantly weaker, with the result that the positive temperature anomalies in El Niño years over North America are much reduced. This weakening is seen both in models with a projected increase and projected decrease in the amplitude of future El Niño events. The mechanisms related to these projected changes, along with potential implications for future long range predictability over North America, will be discussed.</p>


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