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  • Author or Editor: MICHAEL HANTEL x
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Michael Hantel

Abstract

From surface wind estimates published in the Dutch Atlas monthly charts of surface wind vergence over the Indian Ocean down to 50S were computed. Since the original data were smoothed by a low-pass filter, the charts exhibit only regional and large-scale features. The vergence distributions are not zonally symmetric; rather, they show a cell-like structure.

The vergence patterns are discussed in terms of latitudinal-time sections, both for the Arabian Sea and the Bay of Bengal longitude range, and compared with similar plots of the precipitation frequency. North of 10–20S there seem to exist three different circulation regimes, separated by sharply defined transition periods, a characteristic of the Indian monsoon climate. A simple description of this threefold monsoonal rhythm is given in terms of the first and second harmonies of the annual march of temperature.

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Michael Hantel

Abstract

We consider global climate models based on zonally averaged balance relations. Inherent boundary conditions require the meridional fluxes of non-negative properties (temperature, humidity, energy, etc.), as well as the flux of zonal momentum, to vanish at both poles. On the other hand, the meridional divergence of these fluxes does not vanish at either pole. An important exception from this general non-zero polar divergence condition of meridional fluxes is the transport of zonal momentum; the meridional divergence of zonal momentum flux vanishes at the pole because there is neither zonal surface stress nor horizontal wind. These conditions are derived from the balance equations for energy and momentum. Furthermore, they are tested with observed flux data for specific humidity and zonal wind. The closure problem in such models is often overcome by a diffusive parameterization of the fluxes in terms of meridional gradients. It is shown that, due to the above conditions, the exchange coefficient for the energy transport may not vanish at the poles. This has implications for semi-empirical models designed to test climate's stability and transitivity.

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Irene E. Teubner
,
Leopold Haimberger
, and
Michael Hantel

Abstract

Snow cover duration is commonly derived from snow depth, snow water equivalent, or satellite data. Snow cover duration has more recently also been inferred from ground temperature data. In this study, a probabilistic snow cover duration (SCD) model is introduced that estimates the conditional probability for snow cover given the daily mean and the diurnal range of ground temperature. For the application of the SCD model, 87 Austrian sites in the Alpine region are investigated in the period of 2000 to 2011. The daily range of ground temperature is identified to represent the primary variable in determining the snow cover duration. In the case of a large dataset, however, the inclusion of the daily mean ground temperature as the second given parameter improves results. Rank correlation coefficients of predicted versus observed snow cover duration are typically between 0.8 and 0.9.

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