Propagation of the Madden–Julian Oscillation and scale interaction with the diurnal cycle in a high-resolution GCM

Peatman, Simon C.; Matthews, Adrian J.; Stevens, David P.

doi:10.1007/s00382-015-2513-5

Cited by 52 publications

(51 citation statements)

References 47 publications

(69 reference statements)

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“…In addition, the increased resolution enables a more realistic simulation of small-scale phenomena with potentially severe impacts such as tropical cyclones (Shaevitz et al, 2015;Zhao et al, 2009;Bengtsson et al, 2007;Murakami et al, 2015;Walsh et al, 2012;Ohfuchi et al, 2004;Bell et al, 2013;Strachan et al, 2013;Walsh et al, 2015), tropical-extratropical interactions (Baatsen et al, 2015;Haarsma et al, 2013), and polar lows (Zappa et al, 2014). Other phenomena that are sensitive to increasing resolution are ocean mixing, sea-ice dynamics, the diurnal precipitation cycle (Sato et al, 2009;Birch et al, 2014;Vellinga et al, 2016), quasi biennial oscillation (QBO) (Hertwig et al, 2015), the Madden-Julian oscillation (MJO) representation (Peatman et al, 2015), atmospheric low-level coastal jets and their impact on sea surface temperature (SST) bias along eastern boundary upwelling regions Zuidema et al, 2016), and monsoons (Sperber et al, 1994;Lal et al, 1997;Martin, 1999). The improved simulation of climate also results in better representation of extreme events such as heat waves, droughts (Van Haren et al, 2015), and floods.…”

Section: Introductionmentioning

confidence: 99%

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

et al. 2016

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Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes.However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25 • in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs).Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability.The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, "what are the origins and consequences of systematic model biases?", but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

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Section: Introductionmentioning

confidence: 99%

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

et al. 2016

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“…Lastly, the active (phases 3-5) and suppressed (phases 6-8) MJO ampli- tudes for Ranai are plotted. The distinction between active and suppressed phases was determined based on recent studies by Peatman et al (2015) and Birch et al (2016). Because the MJO propagates eastward, its effects have a spatial and temporal nature.…”

Section: Case Study: Ranaimentioning

confidence: 99%

“…Among these are the diurnal cycle of convection, the Madden-Julian Oscillation (MJO; Zhang, 2005), equatorial waves, seasonal monsoons (Misra and Li, 2014), progression of the Intertropical Convergence Zone (ITCZ), the El Niño-Southern Oscillation (ENSO), as well as a host of mesoscale and local circulations. Models have difficulty realistically simulating the propagation of tropical waves through the region in part due to the interactions across scales (Peatman et al, 2014(Peatman et al, , 2015. They have also proven largely unable to reproduce the diurnal cycle of convection, which exhibits a nocturnal maximum over the ocean (Chen and Houze, 1997;Sui et al, 1997;Yang and Slingo, 2001;Dai, 2001).…”

Section: Introductionmentioning

confidence: 99%

Modes of vertical thermodynamic and wind variability over the Maritime Continent

Bukowski

Posselt

Reid³

et al. 2017

Atmos. Chem. Phys.

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Abstract. The Maritime Continent (MC) is an exceedingly complex region from the perspective of both its meteorology and its aerosol characteristics. Convection in the MC is ubiquitous and assumes a wide variety of forms under the influence of an evolving large-scale dynamic and thermodynamic context. Understanding the interaction between convective systems and their environment, both individually and in the aggregate, requires knowledge of the dominant patterns of spatial and temporal variability. Ongoing cloud model ensemble studies require realistic perturbations to the atmospheric thermodynamic state to devise system sensitivities. Apart from modeling studies, evanescent signals in the tropical system are obscured by the underlying broad-scale meteorological variability, which if constrained could illuminate fine-scale physical processes.To this end, radiosonde observations from 2008 to 2016 are examined from three upper-air sounding sites within the MC for the purpose of exploring the dominant vertical temperature, humidity, and wind structures in the region. Principal component analysis is applied to the vertical atmospheric column to transform patterns present in radiosonde data into canonical thermodynamic and wind profiles for the MC. Both rotated and non-rotated principal components are considered, and the emerging structure functions reflect the fundamental vertical modes of short-term tropical variability. The results indicate that while there is tremendous spatial and temporal variability across the MC, the primary modes of vertical thermodynamic and wind variability in the region can be represented in a lower-dimensional subspace. In addition, the vertical structures are very similar among different sites around the region, though different structures may manifest more strongly at one location than another. The results indicate that, while different meteorology may be found in various parts of the MC at any given time, the processes themselves are remarkably consistent. The ability to represent this variability using a limited number of structure functions facilitates analysis of covariability between atmospheric structure and convective systems and also enables future systematic model-based ensemble analysis of cloud development, convection, and precipitation over the MC.

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“…This diurnal cycle of island convection is realistic (Mori et al., ; J.‐H. Qian, ; Yang & Slingo, ); in particular, the timing of convection triggering over the island is well simulated, while many models tend to simulate it too early (Neale & Slingo, ; Peatman et al., ; J.‐H. Qian, ).…”

Section: Introductionmentioning

confidence: 99%

Physical Mechanisms Controlling the Offshore Propagation of Convection in the Tropics: 2. Influence of Topography

Coppin

Bellon

2019

J Adv Model Earth Syst

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A set of idealized convection‐permitting simulations is performed to investigate the influence of topography on the physical mechanisms responsible for the nocturnal offshore propagation of convection around tropical islands. All simulations have an idealized island in the middle of a long channel oceanic domain, with constant sea surface temperature and without rotation. To diagnose the impact of topography, we compare a flat island simulation with two simulations with mountain ranges of different shapes. The topography over the island has a strong impact on the diurnal cycle of convection as clouds tend to remain all day over the highest topography. This weakens the diurnal cycle and the land breeze front and triggers a comparatively less frequent long‐distance offshore propagation of convection. As in the flat simulation, the distance of offshore propagation is particularly sensitive to humidity and temperature at the top of the boundary layer. A shallow circulation that is asymmetric with respect to the island influences the boundary layer top humidity and can favor propagation on one side of the island or the other. These results mimic cloud and precipitation patterns observed prior to the Madden‐Julian Oscillation propagation over the Maritime Continent. The shape of the topography does not seem to influence the offshore propagation of convection significantly except for mountain‐valley breezes that reinforce the land breeze and the establishment of the asymmetric shallow circulation.

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Propagation of the Madden–Julian Oscillation and scale interaction with the diurnal cycle in a high-resolution GCM

Cited by 52 publications

References 47 publications

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

Modes of vertical thermodynamic and wind variability over the Maritime Continent

Physical Mechanisms Controlling the Offshore Propagation of Convection in the Tropics: 2. Influence of Topography

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