Dynamic predictability of intraseasonal variability associated with the Asian summer monsoon

Waliser, Duane E.; Stern, William F.; Schubert, Siegfried D.; Lau, K.-M.

doi:10.1256/qj.02.51

Cited by 101 publications

(41 citation statements)

References 101 publications

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“…Analysis of the Boreal Summer Intraseasonal Oscillation (BSIO; e.g. Yasunari 1979, Knutson et al 1986, Kemball-Cook and Wang 2001, Lawrence and Webster 2002, Straub and Kiladis 2003, Waliser et al 2003c, among many others), which has a major northward propagating component and has its maximum variance in the Asian monsoon region, is beyond the scope of this study.…”

Section: Isolating the Mjo Modementioning

confidence: 99%

Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals

et al. 2006

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This study evaluates the tropical intraseasonal variability, especially the fidelity of The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2-128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG-EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth.Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their "effective static stability" due to diabatic heating. 3The MJO variance approaches the observed value in only two of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its westward counterpart is too small in most of the models, which is consistent with the lack of highly coherent eastward propagation of the MJO in many models. Moreover, the MJO variance in 13 of the 14 models does not come from a pronounced spectral peak, but usually is associated with an overreddened spectrum, which in turn is associated with a too strong persistence of equatorial precipitation. The two models that arguably do best at simulating the MJO are the only ones having convective closures/triggers linked in some way to moisture convergence.4

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Section: Isolating the Mjo Modementioning

confidence: 99%

Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals

et al. 2006

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“…Compared to earlier predictability studies in which an AGCM was used (Waliser et al 2003), the use of a coupled model provides approximately one week of additional predictability. In two-tiered forecasts, ISO convective anomalies develop too soon since they lock on to the prescribed warm SST anomalies.…”

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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“…In particular, a 30-60-day ISO referred to as the MaddenJulian oscillation (MJO; Madden and Julian 1972) has been studied intensively to understand its impacts on low-and midlatitude atmospheric variability (e.g., Sardeshmukh and Hoskins 1988;Hendon and Salby 1994;Berbery and Nogu es-Paegle 1993) because lowfrequency atmospheric variations such as ISOs are expected to have the potential to extend the lead time of medium-range weather forecasts (e.g., Wheeler and Weickmann 2001;Waliser et al 2003;Miura et al 2007). In addition to the 30-60-day ISO, a high-frequency ISO is involved in the summer monsoon variability around South and Southeast Asia (e.g., Krishnamurti and Bhalme 1976;Murakami 1976;Yasunari 1979).…”

Section: Introductionmentioning

confidence: 99%

Mechanism of Orographic Precipitation around the Meghalaya Plateau Associated with Intraseasonal Oscillation and the Diurnal Cycle

Sato

2013

Monthly Weather Review

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Mesoscale processes that cause tremendous amounts of precipitation around the Meghalaya Plateau, northeast India, were investigated using a regional atmospheric model, with a particular focus on the possible role of an intraseasonal oscillation (ISO) and the diurnal cycle. A numerical experiment was conducted using the Weather Research and Forecasting Model (WRF) to simulate a prominent submonthly-scale ISO event observed during June-July 2004. A WRF experiment successfully simulated the timing and magnitude of precipitation during the first active period and subsequent inactive period of the ISO, despite large biases in the second active period. The WRF experiment revealed that the magnitude of prevailing southwesterly winds in the lower troposphere differs significantly between active and inactive periods; strong southwesterly flow transports abundant moisture to the southern slope of the Meghalaya Plateau during the active period, which triggers forced lifting and brings orographic precipitation. However, low-level wind during the inactive period is too weak to overcome the vertical stratification barrier; hence, it is unable to reach the condensation level. The WRF experiment suggested that the diurnal cycle of precipitation is enhanced during the active period, exhibiting an evening to early morning maximum, as observed by the Tropical Rainfall Measuring Mission (TRMM). The experiment also indicated a prominent nocturnal low-level jet (LLJ) appearing at 900 hPa. The direction of the LLJ varies clockwise with time, which accelerates the preexisting southwesterly flow during 1800-0600 LT. The diurnal variation of the LLJ is responsible for the evening to early morning maximum of precipitation, thus contributing to the precipitation variability in the ISO.

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Dynamic predictability of intraseasonal variability associated with the Asian summer monsoon

Cited by 101 publications

References 101 publications

Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals

Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals

Modelling Monsoons: Understanding and Predicting Current and Future Behaviour

Mechanism of Orographic Precipitation around the Meghalaya Plateau Associated with Intraseasonal Oscillation and the Diurnal Cycle

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