Impact of time sampling on atmospheric energy budget residuals

Leopold Haimberger, Bodo Ahrens, Michael Hantel

Diagnostic time-mean budgets of energy and water are evaluated in many atmospheric process studies. The errors of budget-derived quantities like sub-gridscale fluxes or diabatic heating are governed by the errors of the budgets. Here we consider 3D-budgets on the meso-ß scale over Europe. They are compiled from analyses of state quantities available from forecast centres. In the present study we found that the mandatory 6 hours sampling interval between synoptic observations is the main error source for routine time-mean budgets. The errors have been quantified (i) by first sampling forecast data of the German Europamodell every 5 minutes and averaging them over 12 hours (reference budget), and (ii) by sampling the same data only every 6 hours and averaging these also over 12 hours (routine budget). With this method we find that routine budgets in single atmospheric meso-ß scale columns show relative random errors of typically 200% and systematic errors of up to 20%, exclusively due to undersampling. Thus routine budgets, if applied to specific days at individual locations, cannot be expected to yield useful results, except perhaps for cases with extremely strong signal. Compositing over several hundreds of columns with similar weather reduces the random budget error down to about 50%; this seems to be the best one can achieve for routine budgets. The systematic error of some budget quantities is caused by a correlation between the time of occurence of certain processes (mainly convection) and the sampling times. While this error cannot be reduced through compositing, we find that it can be crudely estimated by using different time averaging methods. As application for this method we determine sub-gridscale budget quantities over the BALTEX catchment (August-September 1995) for an ensemble of convectively active and an ensemble of rain-active columns. For the ensemble mean profiles we find, in terms of the diagnosed sub-gridscale test quantities diabatic heating and vertical moist enthalpy flux divergence, that their accuracy is sufficient to detect statistically significant differences between both ensembles. The diabatic heating is about the same for both ensembles, while the flux divergence in the convective ensemble is about three times as large as in the rain ensemble.

Institut für Meteorologie und Geophysik
Meteorology and Atmospheric Physics
Anzahl der Seiten
ÖFOS 2012
Physik, Astronomie
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