The mean-meridional circulation and wave-mean flow interactions in the pressure-isentrope hybrid coordinate (p†) are investigated through an analysis of an annual run of a general circulation model (NCAR CCM1). Special attention is paid to seasonal variations of the circulation and their comparisons between the northern and southern hemispheres. In the troposphere, there are two types of direct circulations, namely, the Hadley cells in low latitudes and direct cells in the extratropics. The latter are almost confined to the troposphere, become strong in winter and have nearly equal magnitude in the two winter hemispheres. These findings indicate that the extratropical cells come mainly from baroclinic instability waves. The stratospheric circulation is of the Brewer-Dobson type and, however, its seasonal evolution is considerably different between the two hemispheres due to the difference in wave activity. The extratropical downward flows in the NH winter are stronger than those in the SH winter and, hence, the global stratosphere-troposphere exchange rate of the air mass has a maximum in the NH winter. Especially inside of the SH circumpolar vortex, downward flows are so weak that the lower stratospheric temperature becomes very low. Such NH-SH asymmetries of downward flows in winter may cause the seasonal variation of the stratospheric temperature even in the tropics through changing tropical upward flows.
Parameter dependence of the sea breeze is discussed by using four types of simplified two-dimensional numerical models; (A) linear and hydrostatic, (B) linear and non-hydrostatic, (C) non-linear and hydrostatic, (D) non-linear and non-hydrostatic models. Various combinations of parameters with regard to the basic situation in the sea breeze are considered. The parameters are the amplitude ΔT, the frequency ω, of the diurnal change of land-surface temperature, the eddy diffusion coefficient t, and the lapse rate of basic potential temperature Γ (or Brunt Vaisala frequency N). Two non-dimensional parameters are a non-linear parameter ε(=ΔT/[Γ(κ/ω)1/2]) and a hydrostatic parameter δ(=ω/N), which appear in the governing equations through a scaling (Niino, 1987). The main conclusions are as follows, (1) The behavior of flows is quite different, depending on whether the set of equations is linear or non-linear. However, there is no serious difference between the cases with and without the hydrostatic assumption under the common sea-breeze parameters. (2) The size of the computation domain plays an important role in determining the scale of the sea breeze. (3) In the non-linear model, the maximum wind velocity of the sea breeze varies in proportion to ε2. When ε is greater than about 3, the maximum wind velocity in the non-linear model becomes much greater than that in the linear model. (4) The maximum wind velocity varies in proportion to δ-1 in both linear and non-linear cases. The dependency on δ slightly differs with ε in the non-linear cases. (5) The maximum Rayleigh number over land during the daytime is estimated to be Ra=0.1ε4δ-2 The computational results suggest that the maximum wind velocity is proportional to Ra1/2 in the non-linear case. Further, the dependence of the maximum wind velocity on the mesh size in the numerical computation is discussed.
An attempt was made to survey the angle of deflection between the surface wind vector (Vs)-the vector mean wind over central Japan, obtained by vectorially averaging the surface wind values at 270 AMeDAS stations-and the geostrophic wind vector (Vg) directly calculated from the surface pressure differences among four stations around central Japan. The value of the mean deflection angle between the two directions was 76 degrees (from Vg to Vs, measured counterclockwise), a relatively large value compared with other studies. The critical direction of Vg, at which the deflection angle significantly changed, was found to occur around ENE. To investigate this critical direction, an attempt was made to relate the angle to surface airflow patterns. It was concluded that the critical direction corresponded to a significant direction of Vg which divides the surface airflow pattern into two categories: the airflow patterns with prevailing NW winds and with prevailing NE winds over the surface of the Kanto plain. The angle of deflection and the wind speed ratio υs/υg were discussed and compared with the results of previous studies.
The time variation of chemical composition of individual aerosol particles (including residues of fog droplets) was examined before, during and after fog events, simultaneously with chemical analysis of fog water, near the top of Mt. Norikura in Japan. In this experiment, particle morphology and the presence of S02-4, N0-3 and NH+4 in individual particles were determined with an electron microscope using thin-film chemical methods. Acidity (pH) measurements showed that the values of bulk fog water were strongly influenced by fog water content, while those of small size fog droplets (γ≤4.0μm) were not. It was found that change in pH is a function of the droplet size. The pH of the smallest droplets (γ≤2.0μm) sometimes reached as low as 1.6 justYbefore fog dissipation. Particle analysis using a thin film chemical method showed that the nitrate ion was detected in fog droplet residues together with the sulfate ion, even if no nitrate-containing particles were found before fog formation. Direct evidence for sulfate production within fog droplets is also presented. Possible processes which lead to the formation of acidic fog droplets are discussed, based on chemical changes of individual aerosol particles during and outside fog events.
Using a physical approach, global ten-day mean long-wave cloud radiative forcing has been derived from satellite data for a period from January 1979 to May 1981. This forcing shows small (2to 3 Wm-2) variations for diurnal, seasonal and inter-annual time scales, even though the detailed structure of cloud fields may have considerable temporal and spatial variability. The amplitude of variations of the hemispheric mean is much larger than the global mean; the largest variation is over land areas (20 Wm-2) of the Southern Hemisphere and the smallest variation is over the ocean (6 Wm-2) of the Northern Hemisphere.