scholarly journals An Evaluation Metric for Intraseasonal Variability and its Application to CMIP3 Twentieth-Century Simulations

2010 ◽  
Vol 23 (13) ◽  
pp. 3497-3508 ◽  
Author(s):  
Prince K. Xavier ◽  
Jean-Philippe Duvel ◽  
Pascale Braconnot ◽  
Francisco J. Doblas-Reyes

Abstract The intraseasonal variability (ISV) is an intermittent phenomenon with variable perturbation patterns. To assess the robustness of the simulated ISV in climate models, it is thus interesting to consider the distribution of perturbation patterns rather than only one average pattern. To inspect this distribution, the authors first introduce a distance that measures the similarity between two patterns. The reproducibility (realism) of the simulated intraseasonal patterns is then defined as the distribution of distances between each pattern and the average simulated (observed) pattern. A good reproducibility is required to analyze the physical source of the simulated disturbances. The realism distribution is required to estimate the proportion of simulated events that have a perturbation pattern similar to observed patterns. The median value of this realism distribution is introduced as an ISV metric. The reproducibility and realism distributions are used to evaluate boreal summer ISV of precipitations over the Indian Ocean for 19 phase 3 of the Coupled Model Intercomparison Project (CMIP3) models. The 19 models are classified in increasing ISV metric order. In agreement with previous studies, the four best ISV metrics are obtained for models having a convective closure totally or partly based on the moisture convergence. Models with high metric values (poorly realistic) tend to give (i) poorly reproducible intraseasonal patterns, (ii) rainfall perturbations poorly organized at large scales, (iii) small day-to-day variability with overly red temporal spectra, and (iv) less accurate summer monsoon rainfall distribution. This confirms that the ISV is an important link in the seamless system that connects weather and climate.

2014 ◽  
Vol 27 (23) ◽  
pp. 8869-8883 ◽  
Author(s):  
J. M. Neena ◽  
Xianan Jiang ◽  
Duane Waliser ◽  
June-Yi Lee ◽  
Bin Wang

Abstract The eastern Pacific (EPAC) warm pool is a region of strong intraseasonal variability (ISV) during boreal summer. While the EPAC ISV is known to have large-scale impacts that shape the weather and climate in the region (e.g., tropical cyclones and local monsoon), simulating the EPAC ISV is still a great challenge for present-day global weather and climate models. In the present study, the predictive skill and predictability of the EPAC ISV are explored in eight coupled model hindcasts from the Intraseasonal Variability Hindcast Experiment (ISVHE). Relative to the prediction skill for the boreal winter Madden–Julian oscillation (MJO) in the ISVHE (~15–25 days), the skill for the EPAC ISV is considerably lower in most models, with an average skill around 10 days. On the other hand, while the MJO exhibits a predictability of 35–45 days, the predictability estimate for the EPAC ISV is 20–30 days. The prediction skill was found to be higher when the hindcasts were initialized from the convective phase of the EPAC ISV as opposed to the subsidence phase. Higher prediction skill was also found to be associated with active MJO initial conditions over the western Pacific (evident in four out of eight models), signaling the importance of exploring the dynamic link between the MJO and the EPAC ISV. The results illustrate the possibility and need for improving dynamical prediction systems to facilitate more accurate and longer-lead predictions of the EPAC ISV and associated weather and short-term climate variability.


2012 ◽  
Vol 25 (20) ◽  
pp. 6942-6957 ◽  
Author(s):  
Jong-Seong Kug ◽  
Yoo-Geun Ham

Abstract Observational studies hypothesized that Indian Ocean (IO) feedback plays a role in leading to a fast transition of El Niño. When El Niño accompanies IO warming, IO warming induces the equatorial easterlies over the western Pacific (WP), leading to a rapid termination of El Niño via an oceanic adjust process. In this study, this IO feedback is reinvestigated using the Coupled Model Intercomparison Project phase 3 (CMIP3) coupled GCM simulations. It is found that most of the climate models mimic this IO feedback reasonably, supporting the observational hypothesis. However, most climate models tend to underestimate the strength of the IO feedback, which means the phase transition of ENSO due to the IO feedback is less effective than the observed one. Furthermore, there is great intermodel diversity in simulating the strength of the IO feedback. It is shown that the strength of the IO feedback is related to the precipitation responses to El Niño and IO SST forcings over the warm-pool regions. Moreover, the authors suggest that the distribution of climatological precipitation is one important component in controlling the strength of the IO feedback.


2021 ◽  
Author(s):  
Lulei Bu ◽  
Zhiyan Zuo ◽  
Ning An

Abstract Our confidence in future climate projection depends on the ability of climate models to simulate the current climate, and model performance in simulating atmospheric circulation affects the ability to simulate extreme events. This study uses the self-organizing map (SOM) method to evaluate the frequency, persistence, and transition characteristics of models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for different ensembles of the 500 hPa daily geopotential height (Z500) in Asia, and then ranks all ensembles according to a comprehensive ranking metric (MR). Our results show that the SOM method is a powerful tool for assessing the daily-scale circulation simulation skills in Asia, and the results are not significantly affected by different map sizes. Positive associations between the performance of ensembles for any two of frequency, persistence, and transition were found, indicating that an ensemble that performs well for one metric is good for the others. The results of the MR ranking show that the r10i1p1f1 ensemble of CanESM5 gives the best overall simulation of 500 hPa circulation in Asia, and this is also the ensemble that best simulates frequency characteristics. The MR simulation skills of the 10 best ensembles for the position of the Western North Pacific Subtropical High (WNPSH) are far better than those of the 10 worst. Such differences may lead to errors in the simulation of extreme events. This study will help future studies in the choice of ensembles with higher circulation simulation skills to improve the credibility of their conclusions.


2012 ◽  
Vol 25 (8) ◽  
pp. 2569-2577 ◽  
Author(s):  
Prince K. Xavier

Abstract A precise relationship between tropospheric moisture and convection is thought to be a key to the accurate simulation of tropical intraseasonal variability. An evaluation of the precipitation distribution and its fundamental physical relationship with relative humidity (RH) in the 14 climate models that participated in the Coupled Model Intercomparison Project phase 3 (CMIP3) is presented here. Most models tend to reside in a light rainfall regime that largely determines the models’ basic state, and the intraseasonal transition toward heavy precipitation is not as gradual as in the observations. Some of the precipitation biases are related to the deficiencies in the representation of the relationship between the precipitation and RH, and the moisture preconditioning ahead of intraseasonal convection. It is also shown that even for models with reasonable baroclinic temperature anomaly structures of the MJO, there are large biases in the intraseasonal specific humidity anomalies, some of which may be related to the uncertainties in representing shallow cumulus, convective downdrafts, and convective detrainment.


2013 ◽  
Vol 26 (17) ◽  
pp. 6185-6214 ◽  
Author(s):  
Meng-Pai Hung ◽  
Jia-Lin Lin ◽  
Wanqiu Wang ◽  
Daehyun Kim ◽  
Toshiaki Shinoda ◽  
...  

Abstract This study evaluates the simulation of the Madden–Julian oscillation (MJO) and convectively coupled equatorial waves (CCEWs) in 20 models from the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and compares the results with the simulation of CMIP phase 3 (CMIP3) models in the IPCC Fourth Assessment Report (AR4). The results show that the CMIP5 models exhibit an overall improvement over the CMIP3 models in the simulation of tropical intraseasonal variability, especially the MJO and several CCEWs. The CMIP5 models generally produce larger total intraseasonal (2–128 day) variance of precipitation than the CMIP3 models, as well as larger variances of Kelvin, equatorial Rossby (ER), and eastward inertio-gravity (EIG) waves. Nearly all models have signals of the CCEWs, with Kelvin and mixed Rossby–gravity (MRG) and EIG waves being especially prominent. The phase speeds, as scaled to equivalent depths, are close to the observed value in 10 of the 20 models, suggesting that these models produce sufficient reduction in their effective static stability by diabatic heating. The CMIP5 models generally produce larger MJO variance than the CMIP3 models, as well as a more realistic ratio between the variance of the eastward MJO and that of its westward counterpart. About one-third of the CMIP5 models generate the spectral peak of MJO precipitation between 30 and 70 days; however, the model MJO period tends to be longer than observations as part of an overreddened spectrum, which in turn is associated with too strong persistence of equatorial precipitation. Only one of the 20 models is able to simulate a realistic eastward propagation of the MJO.


2012 ◽  
Vol 25 (21) ◽  
pp. 7764-7771 ◽  
Author(s):  
Sang-Wook Yeh ◽  
Yoo-Geun Ham ◽  
June-Yi Lee

This study assesses the changes in the tropical Pacific Ocean sea surface temperature (SST) trend and ENSO amplitude by comparing a historical run of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP) phase-5 multimodel ensemble dataset (CMIP5) and the CMIP phase-3 dataset (CMIP3). The results indicate that the magnitude of the SST trend in the tropical Pacific basin has been significantly reduced from CMIP3 to CMIP5, which may be associated with the overestimation of the response to natural forcing and aerosols by including Earth system models in CMIP5. Moreover, the patterns of tropical warming over the second half of the twentieth century have changed from a La Niña–like structure in CMIP3 to an El Niño–like structure in CMIP5. Further analysis indicates that such changes in the background state of the tropical Pacific and an increase in the sensitivity of the atmospheric response to the SST changes in the eastern tropical Pacific have influenced the ENSO properties. In particular, the ratio of the SST anomaly variance in the eastern and western tropical Pacific increased from CMIP3 to CMIP5, indicating that a center of action associated with the ENSO amplitude has shifted to the east.


2011 ◽  
Vol 24 (16) ◽  
pp. 4402-4418 ◽  
Author(s):  
Aaron Donohoe ◽  
David S. Battisti

Abstract The planetary albedo is partitioned into a component due to atmospheric reflection and a component due to surface reflection by using shortwave fluxes at the surface and top of the atmosphere in conjunction with a simple radiation model. The vast majority of the observed global average planetary albedo (88%) is due to atmospheric reflection. Surface reflection makes a relatively small contribution to planetary albedo because the atmosphere attenuates the surface contribution to planetary albedo by a factor of approximately 3. The global average planetary albedo in the ensemble average of phase 3 of the Coupled Model Intercomparison Project (CMIP3) preindustrial simulations is also primarily (87%) due to atmospheric albedo. The intermodel spread in planetary albedo is relatively large and is found to be predominantly a consequence of intermodel differences in atmospheric albedo, with surface processes playing a much smaller role despite significant intermodel differences in surface albedo. The CMIP3 models show a decrease in planetary albedo under a doubling of carbon dioxide—also primarily due to changes in atmospheric reflection (which explains more than 90% of the intermodel spread). All models show a decrease in planetary albedo due to the lowered surface albedo associated with a contraction of the cryosphere in a warmer world, but this effect is small compared to the spread in planetary albedo due to model differences in the change in clouds.


2019 ◽  
Vol 32 (2) ◽  
pp. 639-661 ◽  
Author(s):  
Y. Chang ◽  
S. D. Schubert ◽  
R. D. Koster ◽  
A. M. Molod ◽  
H. Wang

Abstract We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.


2020 ◽  
Author(s):  
Charlotte Pascoe ◽  
David Hassell ◽  
Martina Stockhause ◽  
Mark Greenslade

<div>The Earth System Documentation (ES-DOC) project aims to nurture an ecosystem of tools & services in support of Earth System documentation creation, analysis and dissemination. Such an ecosystem enables the scientific community to better understand and utilise Earth system model data.</div><div>The ES-DOC infrastructure for the Coupled Model Intercomparison Project Phase 6 (CMIP6) modelling groups to describe their climate models and make the documentation available on-line has been available for 18 months, and more recently the automatic generation of documentation of every published simulation has meant that every CMIP6 dataset within the Earth System Grid Federation (ESGF) is now immediately connected to the ES-DOC description of the entire workflow that created it, via a “further info URL”.</div><div>The further info URL is a landing page from which all of the relevant CMIP6 documentation relevant to the data may be accessed, including experimental design, model formulation and ensemble description, as well as providing links to the data citation information.</div><div>These DOI landing pages are part of the Citation Service, provided by DKRZ. Data citation information is also available independently through the ESGF Search portal or in the DataCite search or Google’s dataset search. It provides users of CMIP6 data with the formal citation that should accompany any use of the datasets that comprise their analysis.</div><div>ES-DOC services and the Citation Service form a CMIP6 project  collaboration, and depend upon structured documentation provided by the scientific community. Structured scientific metadata has an important role in science communication, however it’s creation and collation exacts a cost in time, energy and attention.  We discuss progress towards a balance between the ease of information collection and the complexity of our information handling structures.</div><div> </div><div>CMIP6: https://pcmdi.llnl.gov/CMIP6/</div><div>ES-DOC: https://es-doc.org/</div><div>Further Info URL: https://es-doc.org/cmip6-ensembles-further-info-url</div><div> <p>Citation Service: http://cmip6cite.wdc-climate.de</p> </div>


2020 ◽  
Author(s):  
Sophie Nowicki ◽  
Antony J. Payne ◽  
Heiko Goelzer ◽  
Helene Seroussi ◽  
William H. Lipscomb ◽  
...  

Abstract. Projection of the contribution of ice sheets to sea-level change as part of the Coupled Model Intercomparison Project – phase 6 (CMIP6) takes the form of simulations from coupled ice-sheet-climate models and standalone ice sheet models, overseen by the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). This paper describes the experimental setup for process-based sea-level change projections to be performed with standalone Greenland and Antarctic ice sheet models in the context of ISMIP6. The ISMIP6 protocol relies on a suite of polar atmospheric and oceanic CMIP-based forcing for ice sheet models, in order to explore the uncertainty in projected sea-level change due to future emissions scenarios, CMIP models, ice sheet models, and parameterizations for ice-ocean interactions. We describe here the approach taken for defining the suite of ISMIP6 standalone ice sheet simulations, document the experimental framework and implementation, as well as present an overview of the ISMIP6 forcing to be used by participating ice sheet modeling groups.


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