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K. Fraedrich

Abstract

Lateral mixing and compensating subsidence of penetrative convection are two different techniques of parameterizing the large-scale effects of deep cumuli. Both methods are jointly derived by averaging the conservative quantities: total and potential heat separately over the area of the hot towers and the environment. If separated, lateral mixing and compensating subsidence are equivalent with respect to their energetical effect integrated over the large-scale system. Due to this fact the fractional area covered by updrafts results in a simple relation.

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K. Fraedrich
and
E. Kietzig

Abstract

Daily 500 mb geopotentials gridded along 50°S are statistically analyzed for five summer and winter seasons (1959–64): 1) to establish climatic statistics of the macro-turbulent processes in the Southern Hemisphere westwind zone, and 2) to obtain a zonally averaged spectral description of the space-time (wave-number-frequency) structure of midlatitude disturbances of the Southern Hemisphere. In contrast to the Northern Hemisphere, two (instead of three) separated variance maxima are observed in the wavenumber-frequency spectra of the meridional component which contribute to transient eddy variance. They occur in the long (k=4–5,p=6–12 days, c≈ 6 m s−1) and short (k=6–7,p<6 days, c≈ 11 m s−1) period range of eastward traveling waves.

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K. Fraedrich
and
L. M. Leslie

Abstract

The results of a major real-time trial of techniques for the short-term (12 h ahead) prediction of precipitation for the Australian tropical city of Darwin are described. The trial compared current operational manual forecasting procedures with a range of alternative techniques including statistical methods, numerical weather prediction (NWP), and model output statistics (MOS) which were developed specifically for the trial.

The only technique of those tested which exhibited skill, i.e., consistent superiority over climatology and/or persistence, was a Markov chain model used either individually or in linear combination with other methods. Of particular significance was the relatively poor showing in the tropics of the numerical weather prediction model products, which were worse than both persistence and climatology. The results of this real-time trial should be treated with care because of the small sample size involved.

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K. Fraedrich
and
L. M. Leslie

Abstract

A “minimal” model is proposed here for the short-term prediction (up to 12 h ahead) of precipitation occurrence in the tropics. The model is purely statistical, consisting of an optimally weighted linear combination of a Markov chain and persistence. It is minimal in the sense that only surface data are needed, and the computing requirements are almost nil.

In this study the skill of the minimal model, i.e., accuracy relative to climatology and/or persistence, is demonstrated in theory and practice. The model was tested in real time during the 1986/87 Australian monsoon season at the tropical city of Darwin.

Results of the real-time experiment reveal that the minimal model was the only model of those available to the Australian Bureau of Meteorology (including manual forecasts, a regional NWP model, and a model output statistics (MOS) scheme) that exhibited forecast accuracy greater than that of both climatology and persistence.

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K. Fraedrich
,
E. Ruprecht
, and
U. Trunte

Abstract

Certain methods are tested to estimate the divergence of the outflow anvil of tropical cloud clusters. These methods are based on the change of digitized brightness values given by a sequence of satellite pictures. From five consecutive pictures of the geostationary satellite ATS 1 a magnitude of the divergence is deduced which is compatible with the results of other investigations.

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K. Fraedrich
and
L. M. Leslie

Abstract

In this article, the theory is presented for a linear combination of two independent predictive techniques (either probabilistic or binary). It is shown that substantial gains might be expected for optimal weighting of the combination. The theory is general but also is applied to several special cases which may be useful for both short-term weather prediction and long-range forecasting. Using data from a recent operational evaluation of techniques for the short-term predicting of rainfall, a linear combination of two independent predictive techniques gives, in practice, improvement in skill compared with the techniques used individually. In the present case, a Markov chain and a numerical weather prediction (NWP) model were combined. The half-Brier wore of the linear combination was 0.142 compared with individual scores of 0.164 for the Markov chain model and 0.258 for the NWP model. The combined Markov-NWP scheme may provide a possible simple alternative to the MOS approach for predictions up to 12 hours ahead.

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K. Fraedrich
and
L. M. Leslie

Abstract

Probability of precipitation (POP) for the 12 hours 0600 to 1800 local time was predicted for Melbourne each day for the three months (winter) period June-August 1986 using six different techniques. These were: a Markov chain model based on 20 years of three-hourly observations', the Australian region limited-area numerical weather prediction (NWP) model; a weighted linear combination of Markov and NWP models; a model output statistics scheme based on the NWP model; an analogue statistics procedure in which a set of the “best” analogues of the NWP forecast were selected; and the manual “official” Bureau of Meteorology forecast for Melbourne, issued by the duty forecaster.

The six techniques were evaluated and compared in terms of Brier scores and also compared with predictions based on climatology. The results of this operational trial indicate that the skill of the combined Markov-NWP model forecasts considerably exceeds the other techniques. The Markov model was next, followed by the other methods which were close together in skill. Some cam was taken in the interpretation of thew findings as there were differences in lead times associated with the NWP model predictions and the MOS and analogue schemes which were dependent upon it, owing to the operational schedule at Melbourne.

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L. M. Leslie
,
K. Fraedrich
, and
T. J. Glowacki

Abstract

It is demonstrated that the skill of short-term regional numerical forecasts can be predicted on a day-to-day basis. This was achieved by using a statistical regression scheme with the model forecast errors (MFE) as the predictands and the initial analysis, together with the model forecast, at proximate points, as the predictors.

In a first attempt to assess the utility of the method, the technique was applied in a long-term quasi-operational trial to 24 h forecasts of mean sea level pressure in two seasonal periods (one summer and one winter period) on the Australian region forecast domain. Correlation coefficients were computed between the predicted and observed root-mean-square (rms) MFE and were found to be 0.54 and 0.51, respectively, averaged over the full region, for the 90-day summer and winter periods. Using standard Student's t-tests these correlations were shown to be highly significant. In addition, the regional forecasts were divided into four categories of rms MFE, and were verified against the observed rms MFE. Using a contingency table skill score (relative to chance), it was demonstrated that the category forecasts exhibited a very high level of skill.

The procedure also was applied to subdomains of the Australian region grid and it was found that the predictions of model forecast skill were improved further for these local forecasts.

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