Atmospheric Oceanic Sciences

The scaling argument developed by Larichev and Held (1995) for eddy amplitudes and fluxes in a horizontally homogeneous, two-layer model on an f-plane is extended to a beta-plane. In terms of the non-dimensional number x = U/(beta*lambda^2), where lambda is the deformation radius and U is the mean thermal wind, the result for the RMS eddy velocity V, the characteristic wavenumber of the energy-containing eddies and of the eddy-driven jets k, and the magnitude of the eddy diffusivity for potential vorticity D, in the limit x>>1, are as follows: V/U ~ x ; k*lambda ~ 1/x ; D/(U*lambda) ~ x^2. Numerical simulations provide qualitative support for this scaling, but suggest that it underestimates the sensitivity of these eddy statistics to the value of x. A generalization that is applicable to continuous stratification is suggested which leads to the estimates: V ~ 1/(beta T^2); k ~ beta*T; D ~ 1/{[beta^2][T^3]} where T is a time-scale determined by the environment; in particular, it equals lambda/U in the two-layer model and N/(fS) in a continuous flow with uniform shear S and stratification N. This same scaling has also been suggested as relevant to a continuously stratified fluid in the opposite limit, x<<1 (Held, 1980). Therefore, we suggest that it may be of general relevance in planetary atmospheres and in the oceans.

We present a model for variations in atmospheric temperature from time scales of one day to one million years based on a stochastic diffusion (random walk) model of the turbulent transport of heat energy vertically in a coupled atmosphere-ocean model. The predictions of the model are supported by station records and paleoclimatic proxy data of temperature variations.

The interdecadal variability of a stochastically forced four-box model of the oceanic meridional thermohaline circulation (THC) is described and compared to the THC variability in the coupled ocean-atmosphere GCM of Delworth, Manabe, and Stouffer (1993). The box model is placed in a linearly stable thermally dominant mean state under mixed boundary conditions. A linear stability analysis of this state reveals one damped oscillatory THC mode in addition to purely damped modes. The variability of the model under a moderate amount of stochastic forcing, meant to emulate the random variability of the atmosphere affecting the coupled model's interdecadal THC variability, is studied. A linear interpretation, in which the damped oscillatory mode is of primary importance, is sufficient for understanding the mechanism accounting for the stochastically forced variability. Direct comparison of the variability in the box model and coupled GCM reveals common qualitative aspects. Such a comparison supports, although does not verify, the hypothesis that the coupled model's THC variability can be interpreted as the result of atmospheric weather exciting a linear damped oscillatory THC mode.

The power spectrum, S , of horizontal transects of plankton abundance are often observed to have a power-law dependence on wavenumber, k , with exponent close to -2: S(k)∝ k −2 over a wide range of scales. I present power spectral analyses of aircraft lidar measurements of phytoplankton abundance from scales of 1 to 100 km. A power spectrum S(k)∝ k −2 is obtained. As a model for this observation, I consider a stochastic growth equation where the rate of change of plankton abundance is determined by turbulent mixing, modeled as a diffusion process in two dimensions, and exponential growth with a stochastically variable net growth rate representing a fluctuating environment. The model predicts a lognormal distribution of abundance and a power spectrum of horizontal transects S(k)∝ k −1.8 , close to the observed spectrum. The model equation predicts that the power spectrum of variations in abundance in time at a point in space is S(f)∝ f −1.5 (where f is the frequency). Time series analysis of local variations of phytoplankton and zooplankton yield a power-law power spectrum with exponents -1.3 and -1.2, respectively from time scales of one hour to one year. These values are roughly consistent with the model prediction of -1.5. The distribution of abundances is nearly lognormal as predicted. The model may be more generally applicable than for the spatial distribution of plankton. I relate the model predictions to observations of spatial patchiness in vegetation.

It is shown that small, local disturbances of entropy in the atmosphere may give rise to "sound" waves propagating with a velocity which depends on the amplitude ratio of the local relative variations of temperature and volume. This velocity is much smaller than the mean molecular velocity and the usual, adiabatic sound velocity.

As a tool for understanding the meridional circulation of the atmosphere, a two-dimensional ( latitude -- height ) numerical model is used to clarify the relationship between the Hadley circulation and large-scale motions associated with moist convection. The model is based on the primitive equations including the moist process, and two kinds of coordinates are used: the spherical coordinate and the Cartesian coordinate with a uniform rotation. The surface temperature is externally fixed and the troposphere is cooled by the radiation; unstable stratification generates large-scale convective motions. Dependencies on the surface temperature difference from north to south Delta T_s are investigated. The numerical results show that a systematic multi-cell structure exists in every experiment. If the surface temperature is constant (Delta T_s = 0 ), convective motions are organized in the scale of the Rossby deformation radius and their precipitation patterns have a periodicity of the advective time tau_D. As Delta T_s becomes larger, the organized convective system tends to propagate toward warmer regions. The convective cells calculated in the Cartesian coordinate model is very similar to those of the mid-latitudes in the spherical coordinate model. In particular, the Hadley cell can be regarded as the limit of the convective cells in the equatorial latitudes.

Changes in the strength of the thermohaline overturning circulation are associated, by geostrophy, with changes in the east-west pressure difference across an ocean basin. The tropical-polar density contrast and the east-west pressure difference are connected by an adjustment process. In flat-bottomed ocean models the adjustment is associated with viscous, baroclinic Kelvin wave propagation. Weak-high latitude stratification leads to the adjustment having an interdecadal timescale. We reexamine model interdecadal oscillations in the context of the adjustment process, for both constant flux and mixed surface boundary conditions. Under constant surface flux, interdecadal oscillations are associated with the passage of a viscous Kelvin wave around the model domain. Our results suggest the oscillations can be self-sustained by perturbations to the western boundary current arising from the southward boundary wave propagation. Mixed boundary condition oscillations are characterized by the eastward, cross-basin movement of salinity-dominated density anomalies, and the westward return of these anomalies along the northern boundary. We suggest the latter is associated with viscous Kelvin wave propagation. Under both types of boundary conditions, the strength of the thermohaline overturning and the tropical-polar density contrast vary out of phase. We show how the phase relationship is related to the boundary wave propagation. The importance of boundary regions indicates an urgent need to examine the robustness of interdecadal variability in models as the resolution is increased, and as the representation of the coastal, shelf/slope wave guide is improved. (Abriged abstract)

This study illustrates the application of a random strong line (RSL) model of radiative transfer to the interpretation of satellite observations of the upwelling radiation in the 6.3 micron water vapor absorption band. The model, based upon an assemblage of randomly overlapped, strongly absorbing, pressure broadened lines, is compared to detailed radiative transfer calculations of the upper (6.7 micron) tropospheric water vapor radiance and demonstrated to be accurate to within ~ 1.2 K. Similar levels of accuracy are found when the model is compared to detailed calculations of the middle (7.3 micron) and lower (8.3 micron) tropospheric water vapor radiance, provided that the emission from the underlying surface is taken into account. Based upon these results, the RSL model is used to interpret TOVS-observed water vapor radiances in terms of the relative humidity averaged over deep layers of the upper, middle, and lower troposphere. We then present near-global maps of the geographic distribution and climatological variations of upper, middle and lower tropospheric humidity from TOVS for the period 1981-1991. These maps clearly depict the role of large-scale circulation in regulating the location and temporal variation of tropospheric water vapor.

We model the ascent of warm, moist air in the Earth's atmosphere by turbulent convection and expansion with the KPZ equation, familiar in the physics literature on surface growth. Clouds form in domains where the interface between the rising air and its surrounding air achieves an elevation higher than that necessary for condensation. The model predictions are consistent with the perimeter fractal dimension and the cumulative frequency-size distribution of cumulus cloud fields observed from space.

The mechanisms of interaction between the seasonal cycle and ENSO are investigated using the Zebiak and Cane ENSO prediction model. The most dominant seasonal effect is found to be due to the wind divergence field, as determined by the seasonal motion of the ITCZ, through its effect on the atmospheric heating. The next order seasonal effects are due to the seasonality of the background SST and ocean upwelling velocity, and the corresponding mechanisms are analyzed. It is suggested that the seasonal forcing has a first order effect on ENSO's dynamics. Important aspects of the seasonal forcing may be included in idealized delayed oscillator ENSO models by making the model background seasonally shift from stable to unstable states.