Impact of Atmosphere–Ocean Coupling on the Predictability of Monsoon Intraseasonal Oscillations*

Fu, Xiouhua; Wang, Bin; Waliser, Duane E.; Tao, Li

doi:10.1175/jas3830.1

Cited by 140 publications

(90 citation statements)

References 57 publications

(89 reference statements)

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“…The present result suggests that air-sea coupling extends MJO forecasting skill by about 1 week. This finding is basically consistent with the result from our previous predictability study of Fu et al (2007), which showed that air-sea coupling extends monsoon intraseasonal predictability by 1 week.…”

Section: Mjo Forecasting Skills In Three Modelssupporting

confidence: 93%

“…Many previous studies with a hierarchy of models have shown that air-sea coupling improves the simulation and predictability of the MJO (Krishnamurti et al 1988;Flatau et al 1997;Wang and Xie 1998;Waliser et al 1999;Woolnough et al 2000;Fu and Wang 2004;Fu et al 2007Fu et al , 2008Pegion and Kirtman 2008). Using model intraseasonal events as target, Fu et al (2008) showed that the potential predictability of the atmosphere-only runs driven by forecasted daily SST reach very similar level as that of the coupled runs.…”

Section: Important Role Of Air-sea Couplingmentioning

confidence: 98%

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Multi-model MJO forecasting during DYNAMO/CINDY period

Lee

Hsu

et al. 2013

Clim Dyn

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The present study assesses the forecast skill of the Madden-Julian Oscillation (MJO) observed during the period of DYNAMO (Dynamics of the MJO)/CINDY (Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011) field campaign in the GFS (NCEP Global Forecast System), CFSv2 (NCEP Climate Forecast System version 2) and UH (University of Hawaii) models, and revealed their strength and weakness in forecasting initiation and propagation of the MJO. Overall, the models forecast better the successive MJO which follows the preceding event than that with no preceding event (primary MJO). The common modeling problems include too slow eastward propagation, the Maritime Continent barrier and weak intensity. The forecasting skills of MJO major modes reach 13, 25 and 28 days, respectively, in the GFS atmosphere-only model, the CFSv2 and UH coupled models. An equal-weighted multi-model ensemble with the CFSv2 and UH models reaches 36 days. Air-sea coupling plays an important role for initiation and propagation of the MJO and largely accounts for the skill difference between the GFS and CFSv2. A series of forecasting experiments by forcing UH model with persistent, forecasted and observed daily SST further demonstrate that: (1) air-sea coupling extends MJO skill by about 1 week; (2) atmosphere-only forecasts driven by forecasted daily SST have a similar skill as the coupled forecasts, which suggests that if the high-resolution GFS is forced with CFSv2 forecasted daily SST, its forecast skill can be much higher than its current level as forced with persistent SST; (3) atmosphere-only forecasts driven by observed daily SST reaches beyond 40 days. It is also found that the MJO-TC (Tropical Cyclone) interactions have been much better represented in the UH and CFSv2 models than that in the GFS model. Both the CFSv2 and UH coupled models reasonably well capture the development of westerly wind bursts associated with November 2011 MJO and the cyclogenesis of TC05A in the Indian Ocean with a lead time of 2 weeks. However, the high-resolution GFS atmosphere-only model fails to reproduce the November MJO and the genesis of TC05A at 2 weeks' lead. This result highlights the necessity to get MJO right in order to ensure skillful extended-range TC forecasting.

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Section: Mjo Forecasting Skills In Three Modelssupporting

confidence: 93%

Section: Important Role Of Air-sea Couplingmentioning

confidence: 98%

Multi-model MJO forecasting during DYNAMO/CINDY period

Lee

Hsu

et al. 2013

Clim Dyn

Self Cite

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“…As such, knowledge of the initial state of the atmosphere is required, as is air-sea interaction for forecasting ISOs . Figure 2 indicates the potential for 20-30 days of rainfall predictability based on numerical experiments initialized with small perturbations to the initial atmospheric state during different phases of the models ISO (Fu et al 2007). …”

Section: Active/break Cyclesmentioning

confidence: 99%

Modelling Monsoons: Understanding and Predicting Current and Future Behaviour

Turner¹,

Sperber²,

Slingo³

et al. 2011

The Global Monsoon System

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The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in 2 our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal timescales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Niño-Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations -for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes -are essential to realize the full potential of monsoon predictability. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Without aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feed...

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“…Since the MJO is a slow oscillator, it is reasonable to think that the long-range predictability would be from four weeks to two months (e.g., Van den Dool and Saha 1990). The actual skillful prediction of the MJO from numerical and statistical models is currently closer to 15-20 days (e.g., Goswami and Xavier 2003;Fu et al 2007;Jiang et al 2008;Seo et al 2009) with a theoretical upper limit of ;30 days that was put forth by Waliser et al (2003). So, we can likely obtain skillful forecasts of the future state of the MJOI with a lead time of at least two weeks making the MJOI a viable long-term forecast tool.…”

mentioning

confidence: 99%

Assessing the Influence of the MJO on Strong Precipitation Events in Subtropical, Semi-Arid North-Central Chile (30°S)

2012

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Annual precipitation in subtropical, semiarid north-central Chile (308S) during rainy years comprises a few (3-5) strong events in the fall and winter, which are presumably modulated by the Madden-Julian oscillation (MJO). Precipitation from 1979-2009 was recorded daily at three stations along the Elqui Valley. The relationship between the MJO and precipitation is investigated from two perspectives: 1) examining a MJO index (MJOI) based on the actual precipitation events and 2) examining the likelihood of precipitation based on a favorable MJOI. About 80% of the strong precipitation events at the coast in La Serena are related to an active MJO near the central equatorial Pacific. These events are often typified by broad, slow moving synoptic systems in phase with the MJO propagation. Blocking in the far southeast Pacific is associated with precipitation 75% of the time, while deep troughs make up the rest.A relationship between a MJOI and strong rainfall suggests that, though it could be used as a potential diagnostic, the number of cases where there is a favorable MJOI but no precipitation (i.e., false alarms) limits its utility. Additional criteria such as the Southern Oscillation (SO) and Antarctic Oscillation (AAO) phases were used to reject false alarms. Rejecting cases with positive values of the SO index reduced the number of false alarms from 70% to 58%, leaving about two false alarms for every correctly diagnosed event. The AAO index could not discriminate between false alarms and real cases. While a favorable MJOI increases the likelihood of precipitation in the Elqui Valley, false alarms remain problematic.

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Impact of Atmosphere–Ocean Coupling on the Predictability of Monsoon Intraseasonal Oscillations*

Cited by 140 publications

References 57 publications

Multi-model MJO forecasting during DYNAMO/CINDY period

Multi-model MJO forecasting during DYNAMO/CINDY period

Modelling Monsoons: Understanding and Predicting Current and Future Behaviour

Assessing the Influence of the MJO on Strong Precipitation Events in Subtropical, Semi-Arid North-Central Chile (30°S)

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