Oceanic mesoscale variability and atmospheric convection on 10°N in the
eastern Pacific
Tom Farrar
Thesis committee: Bob Weller, Raf Ferrari, Jim Price, John Toole
MIT: 7 Sept., 2006
Air-sea interaction mooring
E. Pacific Warm Pool
Isotherms in main
thermocline
Blue dots are current meters
~60 days
SST
Mooring
(°C)
Wave “crests”
Spring-intensified intraseasonal variability in dynamic Spring-intensified intraseasonal variability in dynamic height near 10height near 10°N in the eastern tropical Pacific has been °N in the eastern tropical Pacific has been previously recognized (Miller et al., 1985; Perigaud, 1990; previously recognized (Miller et al., 1985; Perigaud, 1990; Giese et al., 1994).Giese et al., 1994).
Mesoscale intraseasonal variability on 10°N: background
Farrar and Weller (2006; JGR)
Spring-intensified intraseasonal variability in dynamic height near 10°N in the eastern tropical Pacific has been previously recognized (Miller et al., 1985; Perigaud, 1990; Giese et al., 1994).
Many (at least 4) different hypotheses regarding generation Many (at least 4) different hypotheses regarding generation have been proposed. (More on this later…)have been proposed. (More on this later…)
Mesoscale intraseasonal variability on 10°N: background
Spring-intensified intraseasonal variability in dynamic height near 10°N in the eastern tropical Pacific has been previously recognized (Miller et al., 1985; Perigaud, 1990; Giese et al., 1994).
Many (at least 4) different hypotheses regarding generation have been proposed. (More on this later…)
Characterization of the variability remains inadequate for Characterization of the variability remains inadequate for understanding of causes and consequences.understanding of causes and consequences. Example: Perigaud inferred eastward energy propagation, but Example: Perigaud inferred eastward energy propagation, but
Giese et al. argued for localized wind forcing at the eastern Giese et al. argued for localized wind forcing at the eastern boundary– these two notions cannot both be correctboundary– these two notions cannot both be correct
Mesoscale intraseasonal variability on 10°N: background
I. Quantifying the observed variability (Farrar and Weller, 2006)
A. Annual modulation of the variability
B. The observed dispersion characteristics
(or, interpretation as Rossby waves)
II. Hypotheses for the variability (Farrar and Weller, 2006)
Observed evidence for baroclinic instability
III. The effect of this variability (via SST) on atmospheric convection
The amplitude of the variability is annually modulated and is typically strongest in April.
Farrar and Weller (2006; JGR)
Black asterisks: Peak power at each frequencyWhite asterisks: TOPEX tidal aliases (Schlax and Chelton, 1994)
Spectrum of zonal slope of SSH (a proxy for northward velocity) on 10°N
Westward propagation Eastward propagation
Mean U=-11 cm/sMean U=-12 cm/s
(Surface currents derived from satellite and in situ measurements; Bonjean and Lagerloef, 2002)
Mean climatological zonal surface current
NECNECC
Black asterisks: Peak power at each frequencyWhite asterisks: TOPEX tidal aliases (Schlax and Chelton, 1994)
Westward propagation Eastward propagation
Spectrum of zonal slope of SSH (a proxy for northward velocity) on 10°N
U=-11 cm/s
U=0
Pink lines:l=0
Black lines:l=k
ω=frequencyk=east-west wave numberl=north-south wave numberβ=df/dyLD=deformation radiusU= (steady) geostrophic zonal flow
Black asterisks: Peak power at each frequencyWhite asterisks: TOPEX tidal aliases (Schlax and Chelton, 1994)
Westward propagation Eastward propagation
Spectrum of zonal slope of SSH (a proxy for northward velocity) on 10°N
U=-11 cm/s
U=0
Pink lines:l=0
Black lines:l=k
Signal propagation is consistent with dispersion relation for 1st baroclinic mode Rossby waves in a mean westward flow.
I. Direct wind forcing (Giese et al., 1994)
II. Instability of NEC or NEC/NECC system
A. Baroclinic instability (Philander, 1976)
B. Barotropic instability (Perigaud, 1990 null result)
III. Radiation of Rossby waves from baroclinic coastal Kelvin waves
IV. NECC Retroflection (Hansen and Maul, 1990)
Hypotheses for intraseasonal variability:
?
See Farrar and Weller (2006; JGR) for a more detailed discussion.
Farrar and Weller (2006),
Zamudio et al. (2006)
U1 ρ1
U2 ρ2
H1
H2
Necessary condition for instability of a westward surface current
Since H1/H2≈0.02, a very good approximation to the above condition is: (Or, U1 < -20
cm/s)
2-Layer model of baroclinic instability:
o
gg
'
)(
'
212
212
HHf
HHgLD
21
21
'
f
HgUU
2DLU
U1 ρ1
U2 ρ2
H1
H2
Necessary condition for instability of a westward surface current
Since H1/H2≈0.02, a very good approximation to the above condition is:
2-Layer model of baroclinic instability:
o
gg
'
)(
'
212
212
HHf
HHgLD
21
21
'
f
HgUU
Approach: Is there any correspondence of flow speeds meeting this condition with increased levels of intraseaonal variability?
(Or, U1 < -20 cm/s)
2DLU
Pink lines:
Black lines:
Grey lines:
(eastward)
50-100 day band-passed SSH (color contours, +/-8 cm range)
Surface currents estimated from TOPEX + Levitus dynamic height
black=-15 cm/swhite=-25 cm/s(Ucrit~-20 cm/s)
During every year except 1998, there is a correspondence between Ucrit and the amplitude of the variabilityBaroclinic
instability likely explains the enhanced intraseasonal variability and its annual cycle
Conclusions regarding 10°N Intraseasonal Signal
1. Signal propagation is consistent with dispersion relation for 1st baroclinic mode Rossby waves in a mean westward flow.
2. The timing and location of the variability is consistent with baroclinic instability as a generation mechanism.
Air-sea interaction mooring
SST
(°C)
Not shown (but important for what follows): horizontal advection by this mesoscale variability drives local SST variations
Band-pass filtered buoy data
Surface solar radiation and mixed-layer temperature appear roughly out of phase
Suggests SST may be modulating convection (but this record is too short)
Visible reflectivity Visible reflectivity from GOES-9 satellitefrom GOES-9 satellite <6 months of data<6 months of data
Columnar cloud liquid water (CLW) Columnar cloud liquid water (CLW) from TMI and 3 SSM/I satellitesfrom TMI and 3 SSM/I satellites 8 years of data8 years of data
Surface solar radiationSurface solar radiation from ISCCP (Rossow and Zhang, from ISCCP (Rossow and Zhang,
1995)1995) 20 years of data20 years of data
Examination of the relationship between mesoscale intraseasonal variability on 10°N
and atmospheric convection
Warm SST
Heat
Incident solar
Reflected
Surface solar
SST
(°C)
To start, we’ll inspect the temporal evolution of SST and some of these “cloud properties” along this line
SST (°C) on 10°N (TMI)
SST, zonal high-pass
SST (°C) on 10°N (TMI)
SST, zonal high-pass
21-d average visible reflectivity (GOES)
SST (°C) on 10°N (TMI)
SST, zonal high-pass
21-d average visible reflectivity (GOES)
Contours are warm SST anomalies (from figure on left)
SST (°C) on 10°N (TMI)
SST, zonal high-pass
21-d average visible reflectivity (GOES)
Contours are warm SST anomalies (from figure on left)
SST (°C) on 10°N (TMI)
SST, zonal high-pass
Log10 of cloud liquid water (mm; from TMI and 2 SSM/I satellites)
Contours are warm SST anomalies (from figure on left)
Coherence amplitude of logarithm of CLW and SST on 10°N (8 yrs of data)
Peak power in sea
surface slope (white)
Doppler-shifted Rossby wave
dispersion curve
Black asterisks and black contours indicate statistically significant coherence
SST and log(CLW) are
coherent in the Rossby wave band
Coherence amplitude of surface solar radiation and SST on 10.5°N (20 yrs of data)
Peak power in sea
surface slope (white)
Black asterisks and black contours indicate statistically significant coherence
SST and solar radiation are coherent in the Rossby wave band
But, SST and solar
radiation are expected to be
coherent, in general…
Qt
T
TQ
Coherence phase of surface solar radiation and SST on 10.5°N (20 yrs of data)
Phase angle (deg)
In the Rossby wave band, the coherence phase supports the idea that SST variations drive variations in solar radiation (i.e. clouds)
Outside the Rossby wave band, the phase is consistent with an SST response to solar forcing.
Coherent variability in SST and cloud properties detected in 3 Coherent variability in SST and cloud properties detected in 3 pairs of satellite data sets suggests that oceanic mesoscale pairs of satellite data sets suggests that oceanic mesoscale variability modulates atmospheric convection in the region.variability modulates atmospheric convection in the region.
20-35% of the variance in the logarithm of cloud liquid water at 20-35% of the variance in the logarithm of cloud liquid water at time scales of 50-100 days and zonal scales of ~10° can be time scales of 50-100 days and zonal scales of ~10° can be attributed to mesoscale SST variability.attributed to mesoscale SST variability.
Mesoscale intraseasonal variability on 10°N: relationship to atmospheric convection
Coherent variability in SST and cloud properties detected in 3 pairs of satellite data sets suggests that oceanic mesoscale variability modulates atmospheric convection in the region.
20-35% of the variance in the logarithm of cloud liquid water at time scales of 50-100 days and zonal scales of ~10° can be attributed to mesoscale SST variability.
A few previous studies have related cloud signals to oceanic mesoscale SST signals:
Tropical instability waves (Deser et al., 1993; Hashizume et al., 2001) Near the Southern Ocean (O’Neill et al., 2005)
Many recent studies have detected signals in surface winds related to mesoscale SST signals
e.g., Hayes et al. (1989); Nonaka and Xie (2003); Xie (2004); Small et al. (2005)
One mechanism for the wind signal is destabilization of the atmospheric boundary layer by the SST field The cloud signal is consistent with this mechanism.
Mesoscale intraseasonal variability on 10°N: relationship to atmospheric convection
Conclusion
The energetic mesoscale variability in the E. Pacific warm pool appears to result in part from baroclinic instability of the NEC
Thus, the variability is likely important to the mean heat and momentum balance of this climatically important region
In addition, the variability has a more direct effect on atmospheric convection by modulating SST
E. Pacific Warm Pool
Supplementary slides:
Dispersion curves in 2-layer and 1.5-layer models
Barotropic mode
Baroclinic mode
Growth rate
DLk
1
Pink lines:
Black lines:
Grey lines:
(eastward)
50-100 day band-passed SSH (color contours, +/-8 cm range)
Surface currents estimated from TOPEX + Levitus dynamic height
Pink lines:
Black lines:
Grey lines:
(eastward)
50-100 day band-passed SSH (color contours, +/-8 cm range)
Surface currents estimated from TOPEX + Levitus dynamic height