Shaun Lovejoy

Vertical scaling of temperature, wind and humidity fluctuations: dropsondes from 13 km to the surface of the Pacific Ocean

Observational data were taken in the ‘vertical’ structure at 2 Hz from research dropsondes for temperature, wind speed and relative humidity during the ∼800 s it takes to reach the surface from the ∼13 km altitude of the National Oceanic and Atmospheric Administration (NOAA) Gulfstream 4SP aircraft. The observations were made mainly through the depth of the troposphere above the eastern Pacific Ocean from 15° N to 43° N (dropsondes) and 60° N (aircraft) in 2004. Grand averages of some key figures and of probability distribution functions (PDFs) were formed by compounding the data from the Winter Storms Projects 2004, 2005 and 2006, comprising 246, 324 and 315 (some dropped up to 60° N) useable sondes, respectively. This sizeable data set was used to representatively characterize the statistical fluctuations in the ‘vertical’ structure from 13 km to the surface. The fluctuations are resolved at 5–10 m altitude, so covering up to 3 orders of magnitude of typical tropospheric weighting functions for passive remote sounders. Average ‘vertical’ statistical, multifractal, scaling exponents H, C 1 and α of temperature, wind speed and humidity fluctuations observed at high resolution were computed and are available as potential generators of representative, scale-invariant summaries of the vertical structure of the marine troposphere, for use in design and retrieval of remotely sounded observations.

GENERALISED SCALE INVARIANCE AND ANISOTROPIC INHOMOGENEOUS FRACTALS IN TURBULENCE

A generalisation of scaling is presented to deal with anisotropy and (multidimensional) intermittency. Implications, especially for meteorological fields, are discussed.

CARACTÉRISTIQUES MULTIFRACTALES ET EXTRÊMES DE LA PRÉCIPITATION À HAUTE RÉSOLUTION, APPLICATION À LA DÉTECTION DU CHANGEMENT CLIMATIQUE Multifractal characteristics and extremes of high-resolution rainfall, application to climate change detection

The quality of rainfall statistics, especially the Intensity‑Duration‑Frequency curves, closely depends on the reliability of available data. However, it has been shown that most of the time series obtained with tipping bucket rain gauges have a lower measuring frequency than is normally assumed. This question is particularly important for urban hydrology, where it is important to take into account high frequency fluctuations of rainfall. Preliminary studies showed that the estimated number of floods was lower when low time resolution data were used, compared to number of floods obtained with the help of higher time resolution data. The deficit of high frequency data can lead to apparent breaks in the scaling laws, which unnecessarily and notoriously complicate rainfall modelling. It is therefore essential to quantify the quality of data before using them. We present a SERQUAL procedure that enables us to answer this question and we use this procedure to select sub-series having the qualities required for high-resolution analysis. A multifractal approach is then applied to the selected data to characterize the temporal structure and the extreme behaviour of rainfall. In the present paper we present a reliable estimate of the multifractal parameters of the five‑minute high resolution rainfall data for the four departments in France. These parameters can be used to calibrate or validate statistical and stochastic models. On the other hand, the evolution of the multifractal characteristics can also be used to evaluate the hydrological consequences of climate change. The obtained results show that the influence of climate change on precipitation is not perceptible for the studied periods in Ile-de-France.