Geert Lenderink, Royal Netherlands Meteorological Institute – University of Copenhagen

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Atmospheric complexity > Complex Fluids Seminar > 2017 > Geert Lenderink, Royal...

Geert Lenderink, Royal Netherlands Meteorological Institute

Super Clausius-Clapeyron scaling of extreme hourly convective precipitation: a reflection of essential convective physics?

It is generally accepted that precipitation extremes in a warming climate will enhance due to the larger moisture availability. This moisture content is expected to increase following the maximum “water holding” capacity of the air, the Clausius-Clapeyron (C-C) relation yielding approximately 7% per degree. The increase in precipitation extremes in modeling studies or observed trend analysis is often found to be reasonably close to the C-C prediction. However, present-day precipitation-temperature scaling relations indicate that hourly precipitation extremes may have a response to warming substantially exceeding the C-C relation; for the Netherlands the dependency on surface dew point temperature follows two times the C-C relation. Our hypothesis is that this 2C-C behavior arises from local feedbacks related to the dynamics of convective clouds in response to latent heating. Yet, there is vivid scientific debate on the cause of the 2C-C relation, and alternative explanations have been proposed. These alternative hypotheses are mainly based on the assumption that large-scale processes affecting precipitation intensity are systematically varying with (dew point) temperature. 

In this talk I will discus the observed scaling relations, and show how 2C-C behavior is obtained from observations. Then, I will discus with a simple model how a feedback induced by latent heating could give rise to this behavior.  To further sort out the cause of 2C-C behavior the large-scale processes affecting precipitation intensity are investigated to test whether they could systematically affect the scaling relations. Finally, a cloud tracking algorithm is used to investigate scaling in rain radar data, which gives a better insight in the cloud processes affecting precipitation intensity.