Monsoon intra-seasonal variability in a high-resolution version of Met
                        Office Global Coupled model

Fang, Yongjie; Wu, Peili; Mizielinski, Matthew S.; Roberts, Malcolm; Li, Bo; Xin, Xiaoge; Xiang-wen, Liu

doi:10.1080/16000870.2017.1354661

Cited by 9 publications

(7 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The resulting quadrupole pattern of variability anomaly across the Indian-western Pacific sector resembles that of the seasonal mean bias (Figures 5e and 5f). These patterns are consistent with previous findings, which show that precipitation-latent heat flux feedback acts to reduce the overestimated variability in AGCMs when coupled to ocean models (e.g., Fang et al, 2017;R. Wu & Kirtman, 2005).…”

Section: The Response Of Precipitation Variability To Nudgingsupporting

confidence: 93%

“…Several studies have suggested cross-scale interactions may be fundamental in modulating the Asian monsoon annual cycle. For example, IAV of the seasonal mean monsoon rainfall is affected by the nature of ISV (e.g., Yoo et al 2010), and a realistic representation of these relationship is key for improved seasonal monsoon simulations and predictions (e.g., Achuthavarier & Krishnamurthy, 2010;Fang et al, 2017). Summertime monsoon precipitation variability is closely linked to the occurrence of severe droughts and floods, which have considerable influence on agriculture, economy, and social well-being across Asia (Udmale et al, 2014;Zheng et al, 2006).…”

Section: The Response Of Precipitation Variability To Nudgingmentioning

confidence: 99%

See 1 more Smart Citation

Contrasting the Role of Regional and Remote Circulation in Driving Asian Monsoon Biases in MetUM GA7.1

et al. 2021

View full text Add to dashboard Cite

The Asian monsoon is a key component of the global atmospheric circulation. During the summer, the monsoon southerlies provide around two thirds of the annual precipitation to about half of the world's population, while during the winter northerly winds can lead to cold surges and severe weather (e.g., Li & Yang, 2010;B. Wang 2006). Given the complexity and spatial extent of the monsoon, its simulation has proven to be a challenging task for climate models, as well as a key testbed to evaluate their processes (Sperber et al., 2013).Numerous studies have documented the model monsoon biases, as well as their spatio-temporal evolution with the annual cycle (e.g., Kang & Shukla, 2006;T. Zhou et al., 2009). Many of these shortcomings have been persisting for decades (Ramesh & Goswami, 2014;Song & Zhou, 2014a). These include the excessive summer rainfall over the northwestern Pacific associated with an anomalously weak Western Pacific Subtropical High (WPSH), and a dipole precipitation anomaly over the Indian monsoon region with a rainfall deficit over the subcontinent and excess precipitation over the tropical Indian Ocean (e.g., Rodríguez et al., 2017;Sperber et al., 2013). The pervasiveness of these biases across both coupled and uncoupled models (M. Bollasina & Nigam, 2009;Song & Zhou, 2014b) suggests the underlying causes could be rooted in their atmospheric component. However, there is some evidence that coupled models can better reproduce monsoon precipitation than atmosphere-only models (Kumar et al., 2005;Zou, 2020) from two main reasons: the damped atmospheric interval variability due to negative feedback from the ocean (Z. Q. Zhou et al., 2018) and the compensating effects between atmospheric and sea surface temperature (SST) biases (Prodhomme et al., 2014;Yang et al., 2019).Model biases hinder reliable attribution of past monsoon variations to anthropogenic forcing (e.g., Wilcox et al., 2015), which in turn hampers our confidence in future projections. One of the limiting factors is the interaction between external forcing and internal variability, especially at interannual to decadal time scales (e.g., Deser et al. 2012). Large uncertainties stem from the atmospheric dynamical response Abstract Monsoon precipitation affects nearly half of the world's population, but monsoon biases are a long-standing problem in climate simulations. We apply dynamical nudging either globally or regionally to demonstrate the role of regional and remote circulation in generating Asian monsoon biases in an atmospheric general circulation model. Monsoon precipitation biases are substantially reduced in response to global nudging but may also be exacerbated over the warm oceanic equatorial areas because of unconstrained sub-grid convection. Regional nudging over Asia appears to be more efficient than nudging outside Asia in reducing seasonal precipitation biases over eastern China and India. This suggests a predominant role of local circulation anomalies in generating monsoon precipitation errors in these regions. An exception i...

show abstract

Section: The Response Of Precipitation Variability To Nudgingsupporting

confidence: 93%

Section: The Response Of Precipitation Variability To Nudgingmentioning

confidence: 99%

Contrasting the Role of Regional and Remote Circulation in Driving Asian Monsoon Biases in MetUM GA7.1

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In comparing atmosphere-only to coupled GCM simulations over the summer monsoon regions, autocorrelations of day-to-day rainfall were seen to improve with coupling (Misra, 2008). Air-sea coupling was also shown to significantly improve the simulation of the BSISO (Kemball-Cook et al, 2002;Fu et al, 2003;Fu and Wang, 2004a;Klingaman et al, 2011;DeMott et al, 2014). MetUM GC2 simula-tions at resolutions of 135 and 25 km showed improved mean sea surface temperature and low-level specific humidity with finer atmospheric resolution (Fang et al, 2017).…”

Section: Introductionmentioning

confidence: 93%

Intraseasonal summer rainfall variability over China in the MetUM GA6 and GC2 configurations

et al. 2018

View full text Add to dashboard Cite

Abstract. The simulation of intraseasonal precipitation variability over China in extended summer (May–October) is evaluated based on six climate simulations of the Met Office Unified Model. Two simulations use the Global Atmosphere 6.0 (GA6) and four the Global Coupled 2.0 (GC2) configuration. Model biases are large such that mean precipitation and intraseasonal variability reach twice their observed values, particularly in southern China. To test the impact of air–sea coupling and horizontal resolution, GA6 and GC2 at horizontal resolutions corresponding to ∼25, 60, and 135 km at 50∘ N are analyzed. Increasing the horizontal resolution and adding air–sea coupling have little effect on these biases. Pre-monsoon rainfall in the Yangtze River basin is too strong in all simulations. Simulated rainfall amounts in June are too high along the southern coast and persist in the coastal region through July, with only a weak northward progression. The observed northward propagation of the Meiyu–Baiu–Changma rainband from spring to late summer is poor in all GA6 and GC2 simulations. To assess how well the MetUM simulates spatial patterns of temporally coherent precipitation, empirical orthogonal teleconnection (EOT) analysis is applied to pentad-mean precipitation. Patterns are connected to large-scale processes by regressing atmospheric fields onto the EOT pentad time series. Most observed patterns of intraseasonal rainfall variability are found in all simulations, including the associated observed mechanisms. This suggests that GA6 and GC2 may provide useful predictions of summer intraseasonal variability despite their substantial biases in mean precipitation and overall intraseasonal variance.

show abstract

“…Though the intra-seasonal forecasting skills have been showing signi cant advances in recent years (Lee et al, 2015), understanding and predicting the MISOs remain one of the central tasks of the climate research community (Vitart et al, 2012;Vitart, 2014). The realistic simulation and accurate prediction of the MISOs is still challenging using the present generation of climate models due to inadequate model physics and parameterization (Fang et al, 2017;Li et al, 2018;Mishra et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Signals of northward propagating Monsoon Intra-seasonal Oscillations (MISOs) in the RegCM4.7 CORDEX-CORE simulation over South Asia domain

Ghosh

Miller

Subramaniam

et al. 2022

Preprint

View full text Add to dashboard Cite

The northward propagation of intra-seasonal oscillations (ISO) is closely associated with the seasonal and sub-seasonal cycle of the Indian summer monsoon (ISM). This northward propagating monsoon ISO (MISO) is prominent at 25–90 days during the ISM and are very complex in nature. In this study, we use a simulation with REGional Climate Model v4.7 (RegCM4.7) output to attempt to better understand one of the major modes of ISO during the period 1981 to 2016. The model forced with EIN75 initial and boundary condition and EIN75 SST forcing is found to successfully capture the major signals of MISO. The propagating features of the MISO circulation pattern are broadly characterized using extended empirical orthogonal function (EEOF) and two major MISO indices (MISO-1 and MISO-2). The regions between the Indian subcontinent and the Indian ocean (IO) are found to be crucial for the MISO propagation during the 25–90 day oscillation. Half of the lifecycle of the MISO is found to be 15 days, i.e., the period necessary for the alteration from break phase to active monsoon phase. Simulated MISO indexes in phase space diagrams also reveal northward propagating signals that further help to explain potential mechanisms behind the MISO rainfall propagation from the IO to the Himalayan foothills.

show abstract

Monsoon intra-seasonal variability in a high-resolution version of Met Office Global Coupled model

Cited by 9 publications

References 65 publications

Contrasting the Role of Regional and Remote Circulation in Driving Asian Monsoon Biases in MetUM GA7.1

Contrasting the Role of Regional and Remote Circulation in Driving Asian Monsoon Biases in MetUM GA7.1

Intraseasonal summer rainfall variability over China in the MetUM GA6 and GC2 configurations

Signals of northward propagating Monsoon Intra-seasonal Oscillations (MISOs) in the RegCM4.7 CORDEX-CORE simulation over South Asia domain

Contact Info

Product

Resources

About