Using a 1‐D model to reproduce the diurnal variability of<scp>SST</scp>

Karagali, Ioanna; Høyer, Jacob L.; Donlon, Craig

doi:10.1002/2016jc012542

Cited by 13 publications

(13 citation statements)

References 44 publications

(65 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In incorporating wave breaking into the TKE equation he improved the models' ability to replicate the diurnal cycle. However, other studies have not found this necessary (e.g., Giglio et al, ; Karagali et al, ). Our results show that we are likely underpredicting the magnitude of diurnal warming and to include wave breaking effects would further reduce the diurnal magnitude.…”

Section: Discussionmentioning

confidence: 89%

See 1 more Smart Citation

Modeling the Near‐Surface Diurnal Cycle of Sea Surface Temperature in the Mediterranean Sea

Pimentel

Tse

et al. 2019

JGR Oceans

View full text Add to dashboard Cite

The diurnal cycle of sea surface temperature (SST) is an important component of the ocean-atmosphere system and is necessary for accurately computing air-sea heat fluxes. Ocean temperatures in the near-surface are highly sensitive to atmospheric conditions and can vary significantly depending on time of day. Ocean general circulation models are unable to fully capture the near-surface diurnal SST variability, because they do not possess the necessary vertical structure and resolution. Furthermore, SST observations come from a number of sources that represent the temperature at various near-surface depths. This presents difficulties when assimilating SST observations as well as constructing robust climate records of SST. In this study we model the fine-scale near-surface structure allowing SST comparisons between foundation SST, SST at depth, subskin SST, and skin SST. Hourly model results, forced and initialized using readily available reanalysis data, are from a 2-year period, 2013-2014, over the Mediterranean Sea. Various solar absorption parameterizations are examined, and the resulting SSTs are compared to Spinning Enhanced Visible and InfraRed Imager-derived observations of the skin temperature. Plain Language SummaryThe sea surface temperature (SST) is an important variable of the climate system. It governs the exchange of energy between the ocean and atmosphere. Accurate knowledge of SST is essential for weather and ocean forecasting. The vast majority of our observations of SST are remotely sensed and derived from satellite instruments that record the temperature within the top 1 mm. These observations are complemented by a mixture of ocean moorings and gliders that measure the temperature at various near-surface depths (∼20 cm to 1 m). SSTs are highly sensitive to atmospheric conditions and can vary significantly depending on time of day and near-surface depth. This presents difficulties when combining different observations to construct robust climate records of SST. In addition, large-scale computational models of the ocean typically resolve temperature in a surface layer ∼1 m thick and are unable to fully capture SST variability. It is therefore challenging to properly compare and/or merge modeled SSTs with observed SSTs. To address these challenges, we present a computational model of the fine-scale near-surface ocean structure. The model is tested in the Mediterranean Sea and used to produce a 2-year data set that makes possible SST comparisons at various near-surface depths at any hour of the day.

show abstract

Section: Discussionmentioning

confidence: 89%

“…GOTM has previously been tailored for modeling diurnal variability (Pimentel et al, ), and this is the version of GOTM which we improve further for this current study. More recently, GOTM has also been used by Karagali et al () and Giglio et al () to successfully reproduce diurnal variability of SST at isolated sites with in situ moorings.…”

Section: Modelmentioning

confidence: 99%

Modeling the Near‐Surface Diurnal Cycle of Sea Surface Temperature in the Mediterranean Sea

Pimentel

Tse

et al. 2019

JGR Oceans

View full text Add to dashboard Cite

show abstract

“…Yet Karagali et al . [] show (for different sites) that a nine band solar absorption model performs better than the standard two band scheme in GOTM simulations of diurnal SST.…”

Section: Modelsmentioning

confidence: 99%

The role of wind gusts in upper ocean diurnal variability

et al. 2017

View full text Add to dashboard Cite

Upper ocean processes play a key role in air‐sea coupling, with variability on both short and long time scales. The diurnal cycle associated with diurnal solar insolation and nighttime cooling, may act, along with stochastic wind variability, on upper ocean temperatures and stratification resulting in a diurnal warm layer and a nonlinear rectified effect on longer time scales. This study describes diurnal changes in upper ocean temperature for a location in the equatorial Indian Ocean, using observations from the Dynamics of the Madden‐Julian Oscillation field campaign, a high vertical resolution 1‐D process model, and a diurnal cycling scheme. Solar forcing is the main driver of diurnal variability in upper ocean temperature and stratification. Yet except during nighttime convection, winds with variability on the order of hours (here referred to as “wind gusts”) regulate how fast surface water is mixed to greater depths when daily mean winds are weak. Wind gusts are much stronger than diurnal winds. Even using stochastic wind gusts but no diurnal winds as input in a 1‐D process model yields an estimate of diurnal temperature that compares well with observations. A new version of the Large and Caron (2015) scheme (LC2015) provides an estimate of upper ocean diurnal temperature that is consistent with observations. LC2015 has the advantage of being suitable for implementation in a climate model, with the goal to improve SST estimates, hence the simulated heat flux at the air‐sea interface. Yet LC2015 is not very sensitive to the inclusion or omission of the high‐frequency component of the wind.

show abstract

“…A number of numerical models are available to understand DV events and predict the variability of the DV process. They range from turbulence closure models (e.g., Karagali et al, 2017;Mellor & Yamada, 1982) to Geophysical Research Letters 10.1002/2017GL075008 statistical models (e.g., Gentemann et al, 2003;Price et al, 1987;Webster et al, 1996), to air-sea coupled models (e.g., Noh et al, 2011), and to physical-empirical hybrid models (e.g., Gentemann et al, 2009;Weihs & Bourassa, 2014). In essence, the balance between the net heat flux and wind-driven turbulent mixing over a daily cycle determines the magnitude of SST DV.…”

Section: A Simple DV Modelmentioning

confidence: 99%

Effects of Australian Summer Monsoon on Sea Surface Temperature Diurnal Variation Over the Australian North‐Western Shelf

Wang

Zhang

2017

Geophysical Research Letters

View full text Add to dashboard Cite

Five‐year (2010 to 2014) sea surface temperature (SST) data from the Advanced Very High Resolution Radiometer are used to study the effects of the Australian summer monsoon on SST diurnal variation (DV) over the Australian northwestern shelf (NWS, defined as 105°E–125°E, 25°S–10°S). Strong DV events identified with amplitude of 0.5–2 K were observed over the NWS. A double‐peak seasonal pattern of DV is obtained, with the strongest DV occurring in February/March and October/November. This seasonal DV pattern over the NWS is largely due to the Australian summer monsoon, which reduces the easterly trade wind during the summer monsoonal period, favoring the development of SST DV. Since the monsoon region is distributed globally in the tropical oceans, in the western and eastern North Pacific, as well as in the southern Indian Ocean, we anticipate that strong SST DV may also exist in these parts of coastal oceans.

show abstract

Using a 1‐D model to reproduce the diurnal variability ofSST

Cited by 13 publications

References 44 publications

Modeling the Near‐Surface Diurnal Cycle of Sea Surface Temperature in the Mediterranean Sea

Modeling the Near‐Surface Diurnal Cycle of Sea Surface Temperature in the Mediterranean Sea

The role of wind gusts in upper ocean diurnal variability

Effects of Australian Summer Monsoon on Sea Surface Temperature Diurnal Variation Over the Australian North‐Western Shelf

Contact Info

Product

Resources

About