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Journal ArticleDOI

Madden-Julian Oscillation prediction and teleconnections in the S2S database

01 Jul 2017-Quarterly Journal of the Royal Meteorological Society (John Wiley & Sons, Ltd)-Vol. 143, Iss: 706, pp 2210-2220
TL;DR: In this paper, the Madden Julian Oscillation (MJO) has been diagnosed in the World Weather Research Program (WWRP)/WCRP Sub-seasonal-to-Seasonal prediction project (S2S) database using the Wheeler and Hendon index over the common hindcast period 1999-2010.
Abstract: The Madden Julian Oscillation (MJO) has been diagnosed in the World Weather Research Program (WWRP)/World Climate Research Program (WCRP) Sub-seasonal-to-Seasonal prediction project (S2S) database using the Wheeler and Hendon index (Wheeler and Hendon 2004) over the common hindcast period 1999–2010 The S2S models display skill to predict the MJO between 2 and 4 weeks The majority of S2S models tend to produce a weaker MJO than in ERA Interim, with a phase speed decreasing with lead time All the S2S models produce realistic patterns of MJO teleconnections at 500 hPa, with an increased probability of positive North Atlantic Oscillation (NAO) following an active MJO over the Indian ocean and of negative NAO following an active MJO over the west Pacific However, the amplitude of the MJO teleconnection patterns are significantly weaker than in ERA Interim over the Euro Atlantic sector and are often too strong over the western North Pacific Models with lower horizontal resolution tend to produce weaker teleconnections In the lower stratosphere, several S2S models produce teleconnections which are too strong compared to ERA Interim These results suggest that although the S2S models display significant skill in predicting the MJO propagation beyond two weeks, all the S2S models do not fully exploit the predictability associated to the MJO in the Northern Extratropics, particularly over Europe
Citations
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Journal ArticleDOI
Jean-Christophe Golaz1, Peter M. Caldwell1, Luke Van Roekel2, Mark R. Petersen2, Qi Tang1, Jonathan Wolfe2, G. W. Abeshu3, Valentine G. Anantharaj4, Xylar Asay-Davis2, David C. Bader1, Sterling Baldwin1, Gautam Bisht5, Peter A. Bogenschutz1, Marcia L. Branstetter4, Michael A. Brunke6, Steven R. Brus2, Susannah M. Burrows7, Philip Cameron-Smith1, Aaron S. Donahue1, Michael Deakin8, Michael Deakin9, Richard C. Easter7, Katherine J. Evans4, Yan Feng10, Mark Flanner11, James G. Foucar9, Jeremy Fyke2, Brian M. Griffin12, Cecile Hannay13, Bryce E. Harrop7, Mattthew J. Hoffman2, Elizabeth Hunke2, Robert Jacob10, Douglas W. Jacobsen2, Nicole Jeffery2, Philip W. Jones2, Noel Keen5, Stephen A. Klein1, Vincent E. Larson12, L. Ruby Leung7, Hongyi Li3, Wuyin Lin14, William H. Lipscomb2, William H. Lipscomb13, Po-Lun Ma7, Salil Mahajan4, Mathew Maltrud2, Azamat Mametjanov10, Julie L. McClean15, Renata B. McCoy1, Richard Neale13, Stephen Price2, Yun Qian7, Philip J. Rasch7, J. E. Jack Reeves Eyre6, William J. Riley5, Todd D. Ringler16, Todd D. Ringler2, Andrew Roberts2, Erika Louise Roesler9, Andrew G. Salinger9, Zeshawn Shaheen1, Xiaoying Shi4, Balwinder Singh7, Jinyun Tang5, Mark A. Taylor9, Peter E. Thornton4, Adrian K. Turner2, Milena Veneziani2, Hui Wan7, Hailong Wang7, Shanlin Wang2, Dean N. Williams1, Phillip J. Wolfram2, Patrick H. Worley4, Shaocheng Xie1, Yang Yang7, Jin-Ho Yoon17, Mark D. Zelinka1, Charles S. Zender18, Xubin Zeng6, Chengzhu Zhang1, Kai Zhang7, Yuying Zhang1, X. Zheng1, Tian Zhou7, Qing Zhu5 
TL;DR: Energy Exascale Earth System Model (E3SM) project as mentioned in this paper is a project of the U.S. Department of Energy that aims to develop and validate the E3SM model.
Abstract: Energy Exascale Earth System Model (E3SM) project - U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research; Climate Model Development and Validation activity - Office of Biological and Environmental Research in the US Department of Energy Office of Science; Regional and Global Modeling and Analysis Program of the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research; National Research Foundation [NRF_2017R1A2b4007480]; Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231]; DOE Office of Science User Facility [DE-AC05-00OR22725]; U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]; DOE [DE-AC05-76RLO1830]; National Center for Atmospheric Research - National Science Foundation [1852977];[DE-SC0012778]

437 citations


Cites background from "Madden-Julian Oscillation predictio..."

  • ...The MJO is generally thought to play a role in ENSO initiation (McPhaden et al., 2006), monsoon active break cycles (Annamalai & Slingo, 2001), tropical cyclogenesis (Sobel & Maloney, 2000), and remote teleconnection effects (Vitart, 2017); therefore, its accurate simulation is key....

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Journal ArticleDOI
18 Jul 2018
TL;DR: In this paper, the authors review the growing evidence for a widespread inconsistency between the low strength of predictable signals in climate models and the relatively high level of agreement they exhibit with observed variability of the atmospheric circulation.
Abstract: We review the growing evidence for a widespread inconsistency between the low strength of predictable signals in climate models and the relatively high level of agreement they exhibit with observed variability of the atmospheric circulation. This discrepancy is particularly evident in the climate variability of the Atlantic sector, where ensemble predictions using climate models generally show higher correlation with observed variability than with their own simulations, and higher correlations with observations than would be expected from their small signal-to-noise ratios, hence a ‘signal-to-noise paradox’. This unusual behaviour has been documented in multiple climate prediction systems and in the response to a number of different sources of climate variability. However, we also note that the total variance in the models is often close in magnitude to the observed variance, and so it is not a simple matter of models containing too much variability. Instead, the proportion of Atlantic climate variance that is predictable in climate models appears to be too weak in amplitude by a factor of two, or perhaps more. In this review, we provide a range of examples from existing studies to build the case for a problem that is common across different climate models, common to several different sources of climate variability and common across a range of timescales. We also discuss the wider implications of this intriguing paradox.

204 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a review of the observed characteristics of intraseasonal tropical-extratropical interactions and their associated mechanisms, identifies the significant gaps in this understanding, and recommends new research endeavors to address the remaining challenges.
Abstract: The interactions and teleconnections between the tropical and midlatitude regions on intraseasonal time scales are an important modulator of tropical and extratropical circulation anomalies and their associated weather patterns. These interactions arise due to the impact of the tropics on the extratropics, the impact of the midlatitudes on the tropics, and two-way interactions between the regions. Observational evidence, as well as theoretical studies with models of complexity ranging from the linear barotropic framework to intricate earth system models, suggest the involvement of a myriad of processes and mechanisms in generating and maintaining these interconnections. At this stage, our understanding of these teleconnections is primarily a collection of concepts; a comprehensive theoretical framework has yet to be established. These intraseasonal teleconnections are increasingly recognized as an untapped source of potential sub-seasonal predictability. However, the complexity and diversity of mechanisms associated with these teleconnections, along with the lack of a conceptual framework to relate them, prevent this potential predictability from being translating into realized forecast skill. This review synthesizes our progress in understanding the observed characteristics of intraseasonal tropical–extratropical interactions and their associated mechanisms, identifies the significant gaps in this understanding, and recommends new research endeavors to address the remaining challenges.

193 citations


Additional excerpts

  • ...Vitart (2017) extended the evaluation of MJO-NAO analysis to the 10 S2S models (Vitart et al., 2017) and showed that in the forecasts the MJO teleconnections over the Euro-Atlantic sector are weaker than in observations....

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Journal ArticleDOI
TL;DR: Flash droughts are a recently recognized type of extreme event distinguished by sudden onset and rapid intensification of drought conditions with severe impacts as discussed by the authors, and they unfold on subseasonal-to-seasonal timescales (weeks to months).
Abstract: Flash droughts are a recently recognized type of extreme event distinguished by sudden onset and rapid intensification of drought conditions with severe impacts. They unfold on subseasonal-to-seasonal timescales (weeks to months), presenting a new challenge for the surge of interest in improving subseasonal-to-seasonal prediction. Here we discuss existing prediction capability for flash droughts and what is needed to establish their predictability. We place them in the context of synoptic to centennial phenomena, consider how they could be incorporated into early warning systems and risk management, and propose two definitions. The growing awareness that flash droughts involve particular processes and severe impacts, and probably a climate change dimension, makes them a compelling frontier for research, monitoring and prediction. Flash droughts, which develop over the course of weeks, are difficult to forecast given the current state of subseasonal-to-seasonal prediction. This Perspective offers operational and research definitions, places them in the broader context of climate and suggests avenues for future research.

185 citations

Journal ArticleDOI
TL;DR: The Subseasonal Experiment (SubX) as discussed by the authors is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving sub-seasonal forecasts.
Abstract: The Subseasonal Experiment (SubX) is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving subseasonal forecasts. Seven global m...

158 citations


Cites methods from "Madden-Julian Oscillation predictio..."

  • ...This range of prediction skill411 is similar to the MJO skill of the WWRP/WCRP S2S models, with the exception of the ECMWF412 model which far exceeds the skill of any other S2S or SubX model (Vitart 2017)....

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  • ...The observed NAO index is calculated using 500 hPa240 geopotential height from NCEP/NCAR Reanalysis (Kalnay et al. 1996).241 b. Multi-model Ensemble242 Since the SubX models are initialized on different days, it is challenging to produce a MME243 (e.g. Vitart (2017))....

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References
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Journal ArticleDOI
TL;DR: ERA-Interim as discussed by the authors is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which will extend back to the early part of the twentieth century.
Abstract: ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright © 2011 Royal Meteorological Society

22,055 citations

Journal ArticleDOI
TL;DR: The Twentieth Century Reanalysis (20CR) dataset as discussed by the authors provides the first estimates of global tropospheric variability, and of the dataset's time-varying quality, from 1871 to the present at 6-hourly temporal and 2° spatial resolutions.
Abstract: The Twentieth Century Reanalysis (20CR) project is an international effort to produce a comprehensive global atmospheric circulation dataset spanning the twentieth century, assimilating only surface pressure reports and using observed monthly sea-surface temperature and sea-ice distributions as boundary conditions. It is chiefly motivated by a need to provide an observational dataset with quantified uncertainties for validations of climate model simulations of the twentieth century on all time-scales, with emphasis on the statistics of daily weather. It uses an Ensemble Kalman Filter data assimilation method with background ‘first guess’ fields supplied by an ensemble of forecasts from a global numerical weather prediction model. This directly yields a global analysis every 6 hours as the most likely state of the atmosphere, and also an uncertainty estimate of that analysis. The 20CR dataset provides the first estimates of global tropospheric variability, and of the dataset's time-varying quality, from 1871 to the present at 6-hourly temporal and 2° spatial resolutions. Intercomparisons with independent radiosonde data indicate that the reanalyses are generally of high quality. The quality in the extratropical Northern Hemisphere throughout the century is similar to that of current three-day operational NWP forecasts. Intercomparisons over the second half-century of these surface-based reanalyses with other reanalyses that also make use of upper-air and satellite data are equally encouraging. It is anticipated that the 20CR dataset will be a valuable resource to the climate research community for both model validations and diagnostic studies. Some surprising results are already evident. For instance, the long-term trends of indices representing the North Atlantic Oscillation, the tropical Pacific Walker Circulation, and the Pacific–North American pattern are weak or non-existent over the full period of record. The long-term trends of zonally averaged precipitation minus evaporation also differ in character from those in climate model simulations of the twentieth century. Copyright © 2011 Royal Meteorological Society and Crown Copyright.

3,043 citations


"Madden-Julian Oscillation predictio..." refers methods in this paper

  • ...In order to assess the sensitivity of the MJO bivariate correlation calculation to the choice of the verifying analysis, the MJO indices and the MJO verification have been recomputed for three S2S models (ECMWF, BoM and NCEP) using different reanalysis datasets: 20CRv2C (Compo et al., 2011) and JRA55 (Ebita et al....

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  • ...…of the MJO bivariate correlation calculation to the choice of the verifying analysis, the MJO indices and the MJO verification have been recomputed for three S2S models (ECMWF, BoM and NCEP) using different reanalysis datasets: 20CRv2C (Compo et al., 2011) and JRA55 (Ebita et al., 2011)....

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Journal ArticleDOI
TL;DR: A seasonally independent index for monitoring the Madden-Julian oscillation (MJO) is described in this paper, which is based on a pair of empirical orthogonal functions (EOFs) of the combined fields of near-equatorially averaged 850-hPa zonal wind, 200-hpa zonal winds, and satellite-observed outgoing longwave radiation (OLR) data.
Abstract: A seasonally independent index for monitoring the Madden–Julian oscillation (MJO) is described. It is based on a pair of empirical orthogonal functions (EOFs) of the combined fields of near-equatorially averaged 850-hPa zonal wind, 200-hPa zonal wind, and satellite-observed outgoing longwave radiation (OLR) data. Projection of the daily observed data onto the multiple-variable EOFs, with the annual cycle and components of interannual variability removed, yields principal component (PC) time series that vary mostly on the intraseasonal time scale of the MJO only. This projection thus serves as an effective filter for the MJO without the need for conventional time filtering, making the PC time series an effective index for real-time use. The pair of PC time series that form the index are called the Real-time Multivariate MJO series 1 (RMM1) and 2 (RMM2). The properties of the RMM series and the spatial patterns of atmospheric variability they capture are explored. Despite the fact that RMM1 and RMM...

2,491 citations

Journal ArticleDOI
25 Sep 2008-Nature
TL;DR: Evidence is presented that the main climate intra-seasonal oscillation in the tropics—the Madden–Julian Oscillation—controls part of the distribution and sequences of the four daily weather regimes defined over the North Atlantic–European region in winter.
Abstract: Bridging the traditional gap between the spatio-temporal scales of weather and climate is a significant challenge facing the atmospheric community. In particular, progress in both medium-range and seasonal-to-interannual climate prediction relies on our understanding of recurrent weather patterns and the identification of specific causes responsible for their favoured occurrence, persistence or transition. Within this framework, I here present evidence that the main climate intra-seasonal oscillation in the tropics-the Madden-Julian Oscillation (MJO)-controls part of the distribution and sequences of the four daily weather regimes defined over the North Atlantic-European region in winter. North Atlantic Oscillation (NAO) regimes are the most affected, allowing for medium-range predictability of their phase far exceeding the limit of around one week that is usually quoted. The tropical-extratropical lagged relationship is asymmetrical. Positive NAO events mostly respond to a mid-latitude low-frequency wave train initiated by the MJO in the western-central tropical Pacific and propagating eastwards. Precursors for negative NAO events are found in the eastern tropical Pacific-western Atlantic, leading to changes along the North Atlantic storm track. Wave-breaking diagnostics tend to support the MJO preconditioning and the role of transient eddies in setting the phase of the NAO. I present a simple statistical model to quantitatively assess the potential predictability of the daily NAO index or the sign of the NAO regimes when they occur. Forecasts are successful in approximately 70 per cent of the cases based on the knowledge of the previous approximately 12-day MJO phase used as a predictor. This promising skill could be of importance considering the tight link between weather regimes and both mean conditions and the chances of extreme events occurring over Europe. These findings are useful for further stressing the need to better simulate and forecast the tropical coupled ocean-atmosphere dynamics, which is a source of medium-to-long range predictability and is the Achilles' heel of the current seamless prediction suites.

643 citations


"Madden-Julian Oscillation predictio..." refers background or methods or result in this paper

  • ...Cassou (2008) and Lin et al. (2009) showed that the probability of a positive phase of the NAO is significantly increased about 10 days after the MJO is in Phase 3 (Phase 3 + 10 days), and significantly decreased about 10 days after the MJO is in Phase 7 (Phase 7 + 10 days). The probability of a negative phase of the NAO is decreased (increased) about 10 days after the MJO is in Phase 3 (Phase 7). The impact of the MJO on two other Euro-Atlantic weather regimes, the Atlantic Ridge and Scandinavian blocking, is much weaker. Vitart and Molteni (2010) showed that a set of ECMWF reforecasts using cycle 32R3 displayed realistic MJO teleconnections over the Northern Extratropics, consistent with the observed impacts (Cassou, 2008; Lin et al., 2009), although the impact of the MJO on the NAO was underestimated in the ECMWF model. Lin et al. (2010) further found that the MJO has a significant impact on the intraseasonal NAO skill scores using the ECCC model....

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  • ...Cassou (2008) and Lin et al. (2009) showed that the probability of a positive phase of the NAO is significantly increased about 10 days after the MJO is in Phase 3 (Phase 3 + 10 days), and significantly decreased about 10 days after the MJO is in Phase 7 (Phase 7 + 10 days)....

    [...]

  • ...Vitart and Molteni (2010) showed that a set of ECMWF reforecasts using cycle 32R3 displayed realistic MJO teleconnections over the Northern Extratropics, consistent with the impact Cassou (2008) and Lin et al. (2009) found, but with a lower amplitude in the Euro-Atlantic sector than in ERA-Interim (Dee et al....

    [...]

  • ...…(2010) showed that a set of ECMWF reforecasts using cycle 32R3 displayed realistic MJO teleconnections over the Northern Extratropics, consistent with the impact Cassou (2008) and Lin et al. (2009) found, but with a lower amplitude in the Euro-Atlantic sector than in ERA-Interim (Dee et al., 2011)....

    [...]

  • ...Vitart and Molteni (2010) showed that a set of ECMWF reforecasts using cycle 32R3 displayed realistic MJO teleconnections over the Northern Extratropics, consistent with the impact Cassou (2008) and Lin et al....

    [...]

Journal ArticleDOI
TL;DR: The Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme as discussed by the authors, which is the main deliverable of this project is the establishment of an extensive database containing sub-seasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts.
Abstract: Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days).The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been co...

626 citations

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