Real-Time Monitoring and Prediction of Modes of Coherent Synoptic to Intraseasonal Tropical Variability

By M. Wheeler, K. Weickmann. 2001

197 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/ed4ef132949290861ce00ebf6c04a702aa719625

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Chidong Zhang
2. E. Maloney
3. Duane Waliser
4. F. Vitart
5. Daehyun Kim
6. M. Wheeler
7. David A. Randall
8. Hai Lin

In Global and Planetary Change

1. Chidong Zhang
2. E. Maloney
3. Duane Waliser
4. F. Vitart
5. Daehyun Kim
6. M. Wheeler
7. David A. Randall
8. Hai Lin

In Oceanography

1. F. Vitart
2. Chidong Zhang
3. M. Wheeler
4. E. Maloney
5. Duane Waliser
6. O. Alves
7. Wanqiu Wang
8. H. Hendon

Citations in the corpus

• Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals (2006, background): “The effective static stability is due to the partial cancellation between diabatic heating and adiabatic cooling associated with vertical motion (Gill 1982; Neelin and Held 1987; Emanuel et al. 1994), which would lead to a reduction of the implied equivalent depth of a convecting disturbance (WK; Ha”
• Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2 (2013, methodology): “Recent empirical models show useful predictive skill of MISO and Madden–Julian oscillation (MJO) up to 15–20 days lead time (Wheeler and Weickmann 2001; Waliser et al. 1999, 2003a, b; Goswami and Xavier 2003; Chattopadhyay et al. 2008; Borah et al. 2013).”
• Global Occurrences of Extreme Precipitation and the Madden–Julian Oscillation: Observations and Predictability (2004, unknown): “…realistic representation of the MJO as well as empirical forecast models (Waliser et al. 1999a; Lo and Hendon 2000; Mo 2001; Jones et al. 2004b; Wheeler and Weickmann 2001; Wheeler and Hendon 2004) can potentially use the slow eastward propagation of the MJOs to improve the prediction of…”
• Modulation of South Indian Ocean Tropical Cyclones by the Madden–Julian Oscillation and Convectively Coupled Equatorial Waves (2006, background): “…disturbances have previously been shown to have some predictability up to a few weeks or several days in advance, respectively (Waliser et al. 2003; Wheeler and Weickmann 2001); thus the time scales are quite relevant for extending the current TC predictability provided by numerical…”
• An All-Season Real-Time Multivariate MJO Index: Development of an Index for Monitoring and Prediction (2004, unknown): “A number of recent studies have demonstrated potential for skillful empirical prediction of the MJO, with useful lead times out to about 15–20 days (von Storch and Xu 1990; Waliser et al. 1999; Lo and Hendon 2000; Mo 2001; Wheeler and Weickmann 2001).”
• Forecast Skill of the Madden-Julian Oscillation in Two Canadian Atmospheric Models (2008, methodology): “Forecasts of the MJO with statistical methods are also quite encouraging (e.g., Waliser et al. 1999; Lo and Hendon 2000; Wheeler and Weickmann 2001; Mo 2001; Jones et al. 2004).”
• Tracking Pulses of the Madden–Julian Oscillation (2013, methodology): “7) or MJO spectral filtering (Wheeler and Weickmann 2001) applied to OLR (Fig.”
• Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time‐scales (2008, background): “Statistical models suggest that it is an important source of predictability (Wheeler and Weickmann 2001).”
• Madden—Julian Oscillation prediction and teleconnections in the S2S database (2017, unknown): “Several empirical and statistical models have been developed to predict the MJO (e.g. Waliser et al., 1999; Lo and Hendon, 2000; Mo, 2001; Wheeler and Weickmann, 2001; Jones et al., 2004; Maharaj and Wheeler, 2005; Jiang et al., 2008), with a useful predictive skill of the MJO reaching a lead time…”
• State of the climate in 2010 (2011, background): “Following this event, the intraseasonal variability during August and much of September primarily reflected higher frequency atmospheric Kelvin wave activity (Wheeler and Kiladis 1999; Wheeler and Weickmann 2001).”
• MJO and Convectively Coupled Equatorial Waves Simulated by CMIP5 Climate Models (2013, background): “These so-called convectively coupled equatorial waves (CCEWs) include Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), eastward inertio-gravity (EIG), and westward inertio-gravity (WIG) waves (Takayabu 1994; WK; Kiladis et al. 2009).”
• Prediction of the Madden–Julian oscillation with the POAMA dynamical prediction system (2011, methodology): “Next we examine the dependence of skill on season (Fig. 6). A significant seasonal variation in prediction skill is detected in both POAMA and the statistical VAR model, with generally the highest COR occurring during December–January–February (DJF) and lowest COR during June– July–August (JJA), con”
• The ``Year'' of Tropical Convection (May 2008-April 2010): Climate Variability and Weather Highlights (2012, methodology): “—, and K. M. Weickmann, 2001: Real-time monitoring and prediction of modes of coherent synoptic to intraseasonal tropical variability.”
• Application of MJO Simulation Diagnostics to Climate Models (2009, methodology): “Zhang 2005) and predicting it using statistical and dynamical methods (Jones et al. 2000; Lo and Hendon 2000; Wheeler and Weickmann 2001; Jones et al. 2004; Seo et al. 2005; Waliser 2006; Vitart et al. 2007; Jiang et al. 2008).”