Diurnal variability in the upper ocean - ICOADS · 2008-08-03 · Using the 1D heat & equation of...
Transcript of Diurnal variability in the upper ocean - ICOADS · 2008-08-03 · Using the 1D heat & equation of...
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Chelle L. GentemannPeter J. Minnett
Satellite measurementRadiometric measurements ModelsGlobal distributionAir-sea interactionsConclusions
Diurnal variability in the upper ocean
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What is a daily SST?
Foundation SST
Sunrise
3 K @ 2PM
Diurnal warming aliased onto SST time series (CLIMATE)
0530
073013300830
POES
AQUATRMM
1.5 K
GOESSEVIRI
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S
ST (
K)
Local Time (hrs)
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Upper Ocean Thermal Structure
Foundation SST
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Summary of empirical models
• Bulk – no vertical structure, fast • Turb. Models – vertical structure, slow
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Measurements at the ocean surface
• Few measurements of diurnal warming at the air-sea interface exist
• Most research / model development use in situ observations at depth or extrapolated from 0.5m or 1.0 m to the ocean surface
• Extrapolation done using bulk (PWP, Fairall, Kraus-Turner, or turbulence closure models (Mellor,Yamada / Kantha/Clayson)
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AVHRR diurnal warming
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CG
0
4 2 0 449 632 10 1 insolation local time wind speed ; truncated Fourier Series
as wind increases, equation approaches 0Q <Q equation = 0
t t . uSST ( t ,Q,u ) f ( t )[(Q Q ) . (Q Q ) ]etmi o oQ ; t ; u f ( t )
,
Δ
Gentemann, C. L., C. J. Donlon, et al. (2003). “Diurnal signals in satellite sea surface temperature measurements.” Geophysical Research Letters 30(3): 1140.
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TMI/PF Model and Data
SST
Buo
y (K
)
SST
MW
(K)
S
ST I
R (K
)
Wind speed (m/s) Insolation (W/m2) Local Time (hrs)
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Global Correction
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Low winds
SSM/I wind speeds 1995-1999 highlight regions where indirect validation should be targeted. Average wind speed is 8.3 m/s and 30% of winds are < 6 m/s. 3% of winds are less than 2 m/s.
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4 research cruises + Explorer
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All M-AERI DW
72 days with diurnal warmingAll DW > 4 K from Melville cruise in Gulf of
CaliforniaPeak warming not at peak insolation
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Compare data & models
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TOGA-COARE (F96)2
2
sw
p T
i pT
S
IT
c D
R c ID
g Iτ
ρ
ρ
α
Static stability and mixed layer stability are enforced, but not shear layer instability
Once incoming (solar and LW) heat flux exceeds the outgoing heat flux (sensible, latent, LW radiation, the diurnal warm layer forms a separate layer within the mixed layer
Surface inputs of heat and momentum are confined within this layer.
Using the 1D heat & equation of state you can determine the diurnal heating at the surface
Require the bulk Ri to be 0.65, to determine the depth of the warm layer
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POSH
• Profiles of Surface Heating (POSH) – F96– Absorption– Dissipation of heat/momentum– Structured profiles of temperature within
the warm layer (CG empirical or Kantha/Clayson (WICK) profiles)
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Dimensionless DW profileN
onD
im D
epth
(z) NonDim Heat Content
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Comparison throughout the day
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Peak at solar noon
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Conclusions• The variability in warming and total daily heat available
from the surface are not well represented by a single point such as the KK02 or K96 models
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Conclusions• CG04 model has largest errors in the late afternoon or
evening when there is a sudden drop in wind speed. Diurnal warming is then over estimated by CG04 model
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Conclusions• F96 model is too small and tends to overestimate warming in
afternoon (due to the accumulation of heat)• POSH model responds rapidly to the onset of warming and
decreases realistically in afternoon. Additionally model returns information on warming profile within the warm layer
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Conclusions
Comparisons at solar noon: models do not model variability well
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Conclusions• Accuracy of CG04 model indicates that it is useful,
especially for for polar orbiters w/ 2AM/PM LECT while POSH more useful for geo-stationary satellites, understanding intra-day variability, and vertical structure.
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Global distribution
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Diurnal Time series
• El Nino warm pool / stronger equatorial winds
• La Nina cold tongue / weaker equatorial winds
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Diurnal Time series
• El Nino warm pool / stronger equatorial winds
• La Nina cold tongue / weaker equatorial winds
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Change
• Change in wind patterns lead to changes in the vertical structure of surface heating
• Heat available to atmosphere• Clouds/convection/feedbacks
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Conclusions
• Look at wind fields to understand diurnal variability
• There are air-sea feedbacks: cold SSTs stabilize the MBL, lower wind speeds at surface, which result in more surface warming, destabilizing MBL, increasing winds…..
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conclusions
• In the tropics it is highly likely that in situ observations are affected by diurnal warming.
• We see in ALL buoy arrays clear warming