Statistical dynamics of tropical wind in radiosonde data

T.-Y Koh,Y S Djamil,C.-K Teo

doi:10.5194/acp-11-4177-2011

T.-Y Koh, Y S Djamil + Show 1 more

Open Access

https://doi.org/10.5194/acp-11-4177-2011

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Abstract

Abstract. Weibull distributions were fitted to wind speed data from radiosonde stations in the global tropics. A statistical theory of independent wind contributions was proposed to partially explain the shape parameter k obtained over Malay Peninsula and the wider Equatorial Monsoon Zone. This statistical dynamical underpinning provides some justification for using empirical Weibull fits to derive wind speed thresholds for monitoring data quality. The regionally adapted thresholds retain more useful data than conventional ones defined from taking the regional mean plus three standard deviations. The new approach is shown to eliminate reports of atypically strong wind over Malay Peninsula which may have escaped detection in quality control of global datasets as the latter has assumed a larger spread of wind speed. New scientific questions are raised in the pursuit of statistical dynamical understanding of meteorological variables in the tropics.

Highlights

Radiosonde observations provide arguably the most reliable long-term meteorological data, especially before the advent of satellites
This paper reports our investigations into the statistical dynamics of radiosonde wind data while on-going work on temperature and humidity data will be reported in future publications
It is hoped that the results presented would motivate similar statistical dynamical studies in other tropical regions with sparse data coverage

Summary

Introduction

Radiosonde observations provide arguably the most reliable long-term meteorological data, especially before the advent of satellites. The statistical methods are usually based on mathematics (e.g. by the use of standard deviation to detect outliers) rather than on dynamics (e.g. by examining properties emergent from statistical mechanics). This may be because it is hard to generalize a single global statistical dynamics that is applicable to widely different climatic zones. Adopting the former “statistical mathematical” approach results in smaller regions with denser station network exerting greater influence in the formulation of QC criteria and thresholds than larger regions with more sparse network.

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