Modeling of wave-induced irradiance variability in the upper ocean mixed layer

Hieronymi, Martin; Macke, Andreas

doi:10.5194/os-8-103-2012

Cited by 35 publications

(29 citation statements)

References 53 publications

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“…9e). In rare events, irradiance values of more than 1.5 E d were measured at this depth level under moderate sea conditions (Veal et al, 2010;Hieronymi et al, 2012). According to Figs.…”

Section: Influence Of the Sea State On The Underwater Light Fieldmentioning

confidence: 82%

“…The differences in L m increase with water depth. At 80 m depth, L m is between 5 and 45 m, the mean value is around 30 m. The dependency of the mean fluctuation length on the wave steepness becomes clear, if we recall the focusing effect of single waves again (Hieronymi et al, 2012). The steeper a wave, the closer is its focal point to the sea surface, i.e.…”

Section: Influence Of the Sea State On The Underwater Light Fieldmentioning

confidence: 97%

“…Our work is based on a two-dimensional Monte Carlo model (Hieronymi et al, 2012) whose capability has been verified by in-situ measurements of the underwater light field and by inter-comparison with the widely-used radiative transfer code HydroLight (Mobley, 1994). The model is especially intended for investigations of spatially high resolved light fields underneath any desired wave profiles.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

“…The radiative transfer in water is simulated by means of two model approaches that are explained in detail by Hieronymi et al (2012). At small depths, the underwater light regime is governed by high-frequency and small-scale intensity changes (e.g.…”

Section: Radiative Transfer Modelsmentioning

confidence: 99%

“…The latter describes the mean of the 10 % highest irradiance values; the labelling is motivated by the definition of the significant wave height H s (or H 1/3 ), which is the average height of the one-third highest waves. On the one hand, the significant irradiance enhancement provides a statistically smoothed function of extreme intensity peaks over the water depth; on the other hand, χ 1/10 can be seen as a rough estimate for measured E d maximum values, taking into account that the sampling rates of some radiometers may be insufficient for high-frequency irradiance measurements and that sensor integration times can elongate with increasing water depth (we did E d measurements with a RAMSES-ACC-VIS radiometer (TriOS, Germany) with a spectral range of 320 to 950 nm and effective sampling rates of 2 to 8 s (Hieronymi et al, 2012)). The modelled spatial light fluctuations are subject to a wavenumber analysis (analogous to frequency analysis) in order to characterize the statistical dynamics of the underwater light field and thereby draw conclusions on the influence of associated wave regimes at the sea surface.…”

Section: Fluctuation Parametersmentioning

confidence: 99%

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On the influence of wind and waves on underwater irradiance fluctuations

Hieronymi

Macke

2012

Ocean Sci.

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Abstract. The influence of various wind and wave conditions on the variability of downwelling irradiance E d (490 nm) in water is subject of this study. The work is based on a two-dimensional Monte Carlo radiative transfer model with high spatial resolution. The model assumes conditions that are ideal for wave focusing, thus simulation results reveal the upper limit for light fluctuations. Local wind primarily determines the steepness of capillary-gravity waves which in turn dominate the irradiance variability near the surface. Down to 3 m depth, maximum irradiance peaks that exceed the mean irradiance E d by a factor of more than 7 can be observed at low wind speeds up to 5 m s −1 . The strength of irradiance fluctuations can be even amplified under the influence of higher ultra-gravity waves; thereby peaks can exceed 11 E d . Sea states influence the light field much deeper; gravity waves can cause considerable irradiance variability even at 100 m depth. The simulation results show that under realistic conditions 50 % radiative enhancements compared to the mean can still occur at 30 m depth. At greater depths, the underwater light variability depends on the wave steepness of the characteristic wave of a sea state; steeper waves cause stronger light fluctuations.

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“…9e). In rare events, irradiance values of more than 1.5 E d were measured at this depth level under moderate sea conditions (Veal et al, 2010;Hieronymi et al, 2012). According to Figs.…”

Section: Influence Of the Sea State On The Underwater Light Fieldmentioning

confidence: 82%

Section: Influence Of the Sea State On The Underwater Light Fieldmentioning

confidence: 97%

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Section: Radiative Transfer Modelsmentioning

confidence: 99%

Section: Fluctuation Parametersmentioning

confidence: 99%

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On the influence of wind and waves on underwater irradiance fluctuations

Hieronymi

Macke

2012

Ocean Sci.

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Wave‐induced light field fluctuations in measured irradiance depth profiles: A wavelet analysis

Wei

Lewis

Dommelen³

et al. 2014

JGR Oceans

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Rapid variations in the intensities of light are commonly observed in profiles of downwelling plane irradiance in the ocean. These fluctuations are often treated as noise and filtered out. Here an effort is made to extract the pertinent statistics to quantify the light field fluctuations from vertical profiles of irradiance measured under clear skies. The irradiance data are collected in oceanic and coastal waters using a traditional free-fall downwelling plane irradiance sensor. The irradiance profiles are transformed into timefrequency domain with a wavelet technique. Two signatures including the dominant frequency (<3.5 Hz) and the coefficient of variation of irradiance fluctuations along the water column are identified from the variance spectrum. Both the dominant frequency and the amplitude decrease as the inverse square root of depth, consistent with simple models of wave focusing and data from other studies. Mechanisms contributing to the observed variations and the observational uncertainties are discussed.

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The interplay of thermodynamics and ocean dynamics during ENSO growth phase

et al. 2020

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The growth of El Niño/Southern Oscillation (ENSO) events is determined by the balance between ocean dynamics and thermodynamics. Here we quantify the contribution of the thermodynamic feedbacks to the sea surface temperature (SST) change during ENSO growth phase by integrating the atmospheric heat fluxes over the temporarily and spatially varying mixed layer to derive an offline “slab ocean” SST. The SST change due to ocean dynamics is estimated as the residual with respect to the total SST change. In observations, 1 K SST change in the Niño3.4 region is composed of an ocean dynamical SST forcing of + 2.6 K and a thermodynamic damping of − 1.6 K, the latter mainly by the shortwave-SST (− 0.9 K) and latent heat flux-SST feedback (− 0.7 K). Most climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5) underestimate the SST change due to both ocean dynamics and net surface heat fluxes, revealing an error compensation between a too weak forcing by ocean dynamics and a too weak damping by atmospheric heat fluxes. In half of the CMIP5 models investigated in this study, the shortwave-SST feedback erroneously acts as an amplifying feedback over the eastern equatorial Pacific, resulting in a hybrid of ocean-driven and shortwave-driven ENSO dynamics. Further, the phase locking and asymmetry of ENSO is investigated in the CMIP5 model ensemble. The climate models with stronger atmospheric feedbacks tend to simulate a more realistic seasonality and asymmetry of the heat flux feedbacks, and they exhibit more realistic phase locking and asymmetry of ENSO. Moreover, the almost linear latent heat flux feedback contributes to ENSO asymmetry in the far eastern equatorial Pacific through an asymmetry in the mixed layer depth. This study suggests that the dynamic and thermodynamic ENSO feedbacks and their seasonality and asymmetries are important metrics to consider for improving ENSO representation in climate models.

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Modeling of wave-induced irradiance variability in the upper ocean mixed layer

Cited by 35 publications

References 53 publications

On the influence of wind and waves on underwater irradiance fluctuations

On the influence of wind and waves on underwater irradiance fluctuations

Wave‐induced light field fluctuations in measured irradiance depth profiles: A wavelet analysis

The interplay of thermodynamics and ocean dynamics during ENSO growth phase

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