SURFACE FLUXES
239
water over the salty coastal sea-water and avoids excessively low salinities at OGCM grid-points at river mouths. Rivers such as the Amazon,
Ganges/Brahmaputra, Zaire, Yenisei/Ob and Yangtze, contribute to the
surface density flux in an major way. They each give local freshwater
fluxes in excess of 100mg/m 2 /s (1mg/m 2 /s ≈ 31mm/year), which
produces a density flux approximately equivalent to that of a 100W/m 2
heat flux. Averaged over the entire ocean area of 3.523 × 10 8 km 2 the
equivalent freshwater flux is 3.57mg/m 2 /s, or about 11 cm/year.
3.
Measuring turbulent air-sea fluxes
The portion of a geophysical fluid that is directly influenced by the
presence of a boundary is referred to as a planetary boundary layer
(PBL) and the two most notable examples are the atmospheric (ABL)
and oceanic (OBL). Air-sea turbulent fluxes are actually measured in the
atmospheric surface layer which begins above the direct influence of the
surface roughness elements and ends at about 10% of the ABL height.
The semi-empirical Monin-Obukhov similarity theory is the basis of our
understanding of the physics of this turbulent layer. The theory argues
that in the surface layer the only important turbulence parameters are
the height, z, and the air-sea fluxes. The fundamental turbulent parameters that can be formed from the fluxes are the friction velocity, u ∗ ,
the scales of the turbulent fluctuations of scalars, such as potential temperature, θ ∗ , and specific humidity, q ∗ , and the Monin-Obukhov length
scale, L:
u
∗2 =
| τ |/ρ
u
∗ θ
∗ =
Q H /(ρ c p )
u
∗ q
∗ =
Q L /(ρ Λ)
L = u
∗3 /(κ B o ),
(15)
where κ = 0.4 is von Karman’s constant and c p is the specific heat of
the air. The surface buoyancy flux is given by the latent and sensible
heat fluxes and can be expressed as
B o = g u
∗ θ ∗
θ v
+
q ∗
(q + 0.608 −1 )
,
(16)
where g is gravitational acceleration, θ v = θ (1. + .608q) is the virtual
potential temperature and the factor 0.608 is the ratio of the molecular
weights of dry air and of water vapor minus 1.
Dimensional analysis is very powerful in the surface layer because the
number of parameters is small and comparable to the number of physical
dimensions. It predicts that layer structure when appropriately scaled
239
water over the salty coastal sea-water and avoids excessively low salinities at OGCM grid-points at river mouths. Rivers such as the Amazon,
Ganges/Brahmaputra, Zaire, Yenisei/Ob and Yangtze, contribute to the
surface density flux in an major way. They each give local freshwater
fluxes in excess of 100mg/m 2 /s (1mg/m 2 /s ≈ 31mm/year), which
produces a density flux approximately equivalent to that of a 100W/m 2
heat flux. Averaged over the entire ocean area of 3.523 × 10 8 km 2 the
equivalent freshwater flux is 3.57mg/m 2 /s, or about 11 cm/year.
3.
Measuring turbulent air-sea fluxes
The portion of a geophysical fluid that is directly influenced by the
presence of a boundary is referred to as a planetary boundary layer
(PBL) and the two most notable examples are the atmospheric (ABL)
and oceanic (OBL). Air-sea turbulent fluxes are actually measured in the
atmospheric surface layer which begins above the direct influence of the
surface roughness elements and ends at about 10% of the ABL height.
The semi-empirical Monin-Obukhov similarity theory is the basis of our
understanding of the physics of this turbulent layer. The theory argues
that in the surface layer the only important turbulence parameters are
the height, z, and the air-sea fluxes. The fundamental turbulent parameters that can be formed from the fluxes are the friction velocity, u ∗ ,
the scales of the turbulent fluctuations of scalars, such as potential temperature, θ ∗ , and specific humidity, q ∗ , and the Monin-Obukhov length
scale, L:
u
∗2 =
| τ |/ρ
u
∗ θ
∗ =
Q H /(ρ c p )
u
∗ q
∗ =
Q L /(ρ Λ)
L = u
∗3 /(κ B o ),
(15)
where κ = 0.4 is von Karman’s constant and c p is the specific heat of
the air. The surface buoyancy flux is given by the latent and sensible
heat fluxes and can be expressed as
B o = g u
∗ θ ∗
θ v
+
q ∗
(q + 0.608 −1 )
,
(16)
where g is gravitational acceleration, θ v = θ (1. + .608q) is the virtual
potential temperature and the factor 0.608 is the ratio of the molecular
weights of dry air and of water vapor minus 1.
Dimensional analysis is very powerful in the surface layer because the
number of parameters is small and comparable to the number of physical
dimensions. It predicts that layer structure when appropriately scaled