Journal ArticleDOI
Madden-Julian Oscillation prediction and teleconnections in the S2S database
TLDR
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 Europeread more
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Book ChapterDOI
Forecast Recalibration and Multimodel Combination
TL;DR: It is shown that forecast recalibration and forecast combination are closely related, and a Bayesian regression method to combine multiple forecasts is discussed, which can assign higher combination weights to models that better correlate with the real world, while avoiding overfitting by controlling the overall variability of the combination weights.
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Introducing long‐term trends into subseasonal temperature forecasts through trend‐aware postprocessing
TL;DR: In this article , a trend-aware forecast postprocessing method was used to calibrate and correct the trend in sub-seasonal forecasts, which typically fail to reproduce observed temperature trends.
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Barotropic energy conversion during Indian summer monsoon: implication of Central Indian Ocean Mode Simulation in CMIP6
TL;DR: In this article , the authors examined the simulations of the central Indian Ocean (CIO) mode in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models and found that the rendition of the CIO mode is dominated by kinetic energy conversion from the background to the intraseasonal variability.
Journal ArticleDOI
Ensemble Kalman filter based data assimilation for tropical waves in the MJO skeleton model
TL;DR: In this paper , a constrained ensemble DA method is applied to study the impact of different physical constraints on the state estimation and prediction of the Madden-Julian oscillation (MJO).
Journal ArticleDOI
Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability
TL;DR: In this paper , a cross-spectral analysis identifies coherent intraseasonal relationships between precipitation and VOD, mostly in arid or semi-arid regions where vegetation is water-limited.
References
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Journal ArticleDOI
The ERA-Interim reanalysis: configuration and performance of the data assimilation system
Dick Dee,S. Uppala,Adrian Simmons,Paul Berrisford,Paul Poli,Shinya Kobayashi,Ulf Andrae,Magdalena Balmaseda,Gianpaolo Balsamo,Peter Bauer,Peter Bechtold,Anton Beljaars,L. van de Berg,Jean Bidlot,Niels Bormann,C. Delsol,Rossana Dragani,Manuel Fuentes,Alan J. Geer,Leopold Haimberger,Sean Healy,Hans Hersbach,Elías Hólm,Lars Isaksen,P. Kallberg,Martin Köhler,Marco Matricardi,A. P. McNally,B. M. Monge-Sanz,Jean-Jacques Morcrette,B.-K. Park,Carole Peubey,P. de Rosnay,Christina Tavolato,Jean-Noël Thépaut,Frederic Vitart +35 more
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.
Journal ArticleDOI
The Twentieth Century Reanalysis Project
Gilbert P. Compo,Gilbert P. Compo,Jeffrey S. Whitaker,Prashant D. Sardeshmukh,Prashant D. Sardeshmukh,N. Matsui,N. Matsui,Rob Allan,Xiaojun Yin,Byron E. Gleason,Russell S. Vose,Glenn Rutledge,P. Bessemoulin,Stefan Brönnimann,Stefan Brönnimann,Manola Brunet,Manola Brunet,R. Crouthamel,Andrea Grant,Pavel Ya. Groisman,Pavel Ya. Groisman,Philip Jones,Michael C. Kruk,Andries Kruger,Gareth J. Marshall,Maurizio Maugeri,H. Mok,Øyvind Nordli,Tom Ross,Ricardo M. Trigo,Xiaolan L. Wang,Scott D. Woodruff,Steven J. Worley +32 more
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.
Journal ArticleDOI
An All-Season Real-Time Multivariate MJO Index: Development of an Index for Monitoring and Prediction
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.
Journal ArticleDOI
Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation
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.
Journal ArticleDOI
The Subseasonal to Seasonal (S2S) Prediction Project Database
Frederic Vitart,Constantin Ardilouze,A. Bonet,Anca Brookshaw,M. Chen,C. Codorean,Michel Déqué,Laura Ferranti,E. Fucile,Manuel Fuentes,Harry H. Hendon,J. Hodgson,H.-S. Kang,Arun Kumar,Hai Lin,Guoqiang Liu,Xiangwen Liu,Piero Malguzzi,I. Mallas,M. Manoussakis,D. Mastrangelo,Craig MacLachlan,Peter McLean,A. Minami,R. Mladek,Tetsuo Nakazawa,S. Najm,Y. Nie,Michel Rixen,Andrew W. Robertson,Paolo Ruti,C. Sun,Yuhei Takaya,Mikhail A. Tolstykh,F. Venuti,Duane E. Waliser,Steven J. Woolnough,Tongwen Wu,D.-J. Won,H. Xiao,R. B. Zaripov,L. Zhang +41 more
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.
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The ERA-Interim reanalysis: configuration and performance of the data assimilation system
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