Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 1: a diurnally forced OGCM

Bernie, Dan; Guilyardi, Éric; Madec, Gurvan; Slingo, Julia; Woolnough, Steven J.

doi:10.1007/s00382-007-0249-6

Cited by 107 publications

(112 citation statements)

References 34 publications

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“…Sui et al (1997) suggested that the asymmetric heating of the upper ocean causes the diurnal variations in SST to influence intraseasonal SST variability. Bernie et al (2005Bernie et al ( , 2007 confirmed this using an idealized 1D ocean model and a primitiveequation ocean general circulation model (OGCM), showing that allowing diurnal SST variations leads to amplified intraseasonal SST variations .…”

Section: Introductionmentioning

confidence: 68%

“…It is possible that our unusually high vertical resolution in the upper ocean and hourly sampling is still insufficient to accurately represent the observed dSST. However, previous studies by Bernie et al (2005) showed that 90% of the observed dSST can be captured by the vertical resolution in the upper ocean of 1 m and the surface fluxes of temporal resolution of 3 h. The diminished dSST would be more likely due to stronger surface wind speed in the model (2.4 m s…”

Section: B Diurnal Cycle In Sstmentioning

confidence: 86%

“…Figure 2a shows the maps of amplitude of diurnal SST fluctuation (dSST) from CF1 for 15-19 November 2011, corresponding to the period before the arrival of the MJO2 deep convection in the DYNAMO region. Note that dSST is defined following Bernie et al (2005) as the difference between the daytime maximum SST and the mean of the preceding and following nighttime minimum SSTs. According to this definition, the dSST in CF24 is not necessarily zero, although it is rather small (Table 2), as the calculation involves the nighttime minimum temperatures over two consecutive days.…”

Section: A Simulated Mjo In Scoarmentioning

confidence: 99%

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Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden–Julian Oscillation

et al. 2014

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This study quantifies, from a systematic set of regional ocean-atmosphere coupled model simulations employing various coupling intervals, the effect of subdaily sea surface temperature (SST) variability on the onset and intensity of Madden-Julian oscillation (MJO) convection in the Indian Ocean. The primary effect of diurnal SST variation (dSST) is to raise time-mean SST and latent heat flux (LH) prior to deep convection. Diurnal SST variation also strengthens the diurnal moistening of the troposphere by collocating the diurnal peak in LH with those of SST. Both effects enhance the convection such that the total precipitation amount scales quasi-linearly with preconvection dSST and time-mean SST. A column-integrated moist static energy (MSE) budget analysis confirms the critical role of diurnal SST variability in the buildup of column MSE and the strength of MJO convection via stronger time-mean LH and diurnal moistening. Two complementary atmosphere-only simulations further elucidate the role of SST conditions in the predictive skill of MJO. The atmospheric model forced with the persistent initial SST, lacking enhanced preconvection warming and moistening, produces a weaker and delayed convection than the diurnally coupled run. The atmospheric model with prescribed daily-mean SST from the coupled run, while eliminating the delayed peak, continues to exhibit weaker convection due to the lack of strong moistening on a diurnal basis. The fact that time-evolving SST with a diurnal cycle strongly influences the onset and intensity of MJO convection is consistent with previous studies that identified an improved representation of diurnal SST as a potential source of MJO predictability.

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Section: Introductionmentioning

confidence: 68%

Section: B Diurnal Cycle In Sstmentioning

confidence: 86%

Section: A Simulated Mjo In Scoarmentioning

confidence: 99%

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Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden–Julian Oscillation

et al. 2014

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“…In their simulations, the MJO is also improved, resulting from the increase in intraseasonal SST variability that stems from the improved diurnal SST variability (Bernie et al 2007). These and other studies (e.g., Klingaman et al 2011) concluded that a very fine vertical grid spacing, of approximately 1 m, is required in the upper layers of the ocean component to resolve the diurnal warm layer processes there.…”

Section: Introductionmentioning

confidence: 99%

The Surface Diurnal Warm Layer in the Indian Ocean during CINDY/DYNAMO

et al. 2014

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) and preferentially in the inactive stage of the Madden-Julian oscillation. Its diurnal harmonic has an exponential vertical structure with a depth scale of 4-5 m (dependent on chlorophyll concentration), consistent with forcing by absorption of solar radiation. The effective sea surface temperature (SST) anomaly due to the diurnal warm layer often reaches 0.88C in the afternoon, with a daily mean of 0.28C, rectifying the diurnal cycle onto longer time scales. This SST anomaly drives an anomalous flux of 4 W m 22 that cools the ocean. Alternatively, in a climate model where this process is unresolved, this represents an erroneous flux that warms the ocean. A simple model predicts a diurnal warm layer to occur on 30%-50% of days across the tropical warm pool. On the remaining days, with low solar radiation and high wind speeds, a residual diurnal cycle is observed by the Seaglider, with a diurnal harmonic of temperature that decreases linearly with depth. As wind speed increases, this already weak temperature gradient decreases further, tending toward isothermal conditions.

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“…The extremes resulting from atmospheric turbulence or the diurnal cycle can also influence the simulated climate. Bernie et al (2007) found that extremes related to the diurnal cycle of solar insolation affect the mixed layer depth and increase the sea surface temperature. These previous works, although not directly addressing changes in fluxes due to enhanced coupling frequency, clearly demonstrate the importance of the basic statistics of the air-sea fluxes for the climate system.…”

Section: Introductionmentioning

confidence: 99%

Air–sea fluxes in a climate model using hourly coupling between the atmospheric and the oceanic components

2016

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We analyse the changes in the air–sea fluxes of momentum, heat and fresh water flux caused by increasing the ocean–atmosphere coupling frequency from once per day to once per hour in the Max Planck Institute Earth System Model. We diagnose the relative influences of daily averaging and high-frequency feedbacks on the basic statistics of the air–sea fluxes at grid point level and quantify feedback modes responsible for large scale changes in fluxes over the Southern Ocean and the Equatorial Pacific. Coupling once per hour instead of once per day reduces the mean of the momentum-flux magnitude by up to 7 % in the tropics and increases it by up to 10 % in the Southern Ocean. These changes result solely from feedbacks between atmosphere and ocean occurring on time scales shorter than 1 day. The variance and extremes of all the fluxes are increased in most parts of the oceans. Exceptions are found for the momentum and fresh water fluxes in the tropics. The increases result mainly from the daily averaging, while the decreases in the tropics are caused by the high-frequency feedbacks. The variance increases are substantial, reaching up to 50 % for the momentum flux, 100 % for the fresh water flux, and a factor of 15 for the net heat flux. These diurnal and intra-diurnal variations account for up to 50–90 % of the total variances and exhibit distinct seasonality. The high-frequency coupling can influence the large-scale feedback modes that lead to large-scale changes in the magnitude of wind stress over the Southern Ocean and Equatorial Pacific. In the Southern Ocean, the dependence of the SST-wind-stress feedback on the mean state of SST, which is colder in the experiment with hourly coupling than in the experiment with daily coupling, leads to an increase of westerlies. In the Equatorial Pacific, Bjerknes feedback in the hourly coupled experiment reveals a diurnal cycle during the El Niño events, with the feedback being stronger in the nighttime than in the daytime and no clear diurnal cycle during the La Niña events. This asymmetry might lead to the decrease of wind stress in the Equatorial Pacific in the hourly coupled experiment. © 2016 The Author(s

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Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 1: a diurnally forced OGCM

Cited by 107 publications

References 34 publications

Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden–Julian Oscillation

Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden–Julian Oscillation

The Surface Diurnal Warm Layer in the Indian Ocean during CINDY/DYNAMO

Air–sea fluxes in a climate model using hourly coupling between the atmospheric and the oceanic components

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