NG54A-01
Estimating Intermittency Exponent in Neutrally Stratified Atmospheric Surface Layer Flows: A Robust Framework Based on Magnitude Cumulant and Surrogate Analyses
This study proposes a novel framework based on magnitude cumulant and surrogate analyses to reliably detect and estimate the intermittency coefficient from turbulent time series and spatial fields. Intermittency coefficients estimated from a large number of neutrally stratified atmospheric surface layer turbulent series from various field campaigns and a dynamic large-eddy model simulated fields are shown to remarkably concur with well-known laboratory experimental results. In addition, a surrogate-based hypothesis testing framework is proposed and shown to significantly reduce the likelihood of detecting a spurious non-zero intermittency coefficient from non- intermittent series and fields. The discriminatory power of the proposed framework is promising for addressing the unresolved question of how atmospheric stability affects the intermittency properties of boundary layer turbulence.
NG54A-02 INVITED
Multi-Scale Variability of Orographic Precipitation and Topographic Attributes: A Wavelet Deconvolution Approach for Rainfall Downscaling
Stochastic downscaling requires a priori knowledge of the way in which rainfall statistics vary across scales. For orographic rainfall, these statistics are influenced by the interaction of the larger scale meteorological forcing with the underlying terrain. In this study we use wavelet-based multiresolution analysis to extract the signature that topography leaves on the multiscale structure of rainfall fields and to construct a scale and time- dependent transfer function (kernel) relating topographic attributes to precipitation. The application of this transfer function to the readily available topography data produces that fraction of the sub-grid scale precipitation variability that is mostly explainable by the terrain, leaving the remaining variability to be explained by scale-invariant parameterizations and reconstructed by conventional stochastic downscaling techniques.
NG54A-03 INVITED
The Deep Impact of Cloud Turbulence (and Microphysics) on Solar Radiation Transport: An Asymptotic Scaling Analysis
Clouds have a first-order role in the balance of the Earth's climate system both in the hydrological and energy (radiation) budget. Yet their representation in climate models, as well as in remote sensing retrievals of their condensed water content, is beyond simplistic: uniform plane-parallel slabs with infinite horizontal extent, irrespective of the scale of computational or observation resolution. At best, a nominal cloud fraction is used to account for unresolved variability, and sometimes 1-point cloud optical depth variability is accounted for; very rarely are spatial correlations even considered. Notwithstanding, the turbulence of Earth's cloudy atmosphere exhibits even to the most casual observer spatial correlations across broad ranges of scales, and these can often be quantified by power-law scaling relations (viz. wavenumber spectra typically in 1/k5/3). A straightforward corollary of such scaling is stochastic continuity (almost everywhere) of the cloud field, as sampled in situ by aircraft as well as remotely with air- and space-borne remote sensing instruments. I will show that, as long as the scaling range contains the scales that matter optically (most importantly, the photon mean- free-path), this quasi-universal behavior has nontrivial consequences for the mean flow of radiation in the cloudy atmosphere. Indeed, the basic propagation kernel in integral radiative transfer equation is no longer exponential but, given the nature of the observed variability, a step distribution with a power-law tail. From there, new scaling laws follow for domain-average radiation properties at wavelengths dominated by multiple scattering using (1) Lévy's generalizations of the central limit theorem to infinite variance steps, (2) the Sparre-Anderson/Frisch law for first passages of random walks in a half-space, and (3) an ansatz that accounts for the finite thickness of the cloudy atmosphere. Recent observations of solar photon path length statistics using O2transmission spectroscopy and numerical simulations are used to assess the relevance of the new asymptotic scaling relations to the real atmosphere. An interesting evolution of the mean-field radiation transport model ensues. The analytic theory remains qualitatively correct and makes important predictions for the impact of spatially variable cloudiness on path length statistics for reflected sunlight. Such observations will become available none to soon in 2008 when NASA's Orbiting Carbon Observatory (OCO) carries first high-resolution oxygen A-band spectrometer into space.
NG54A-04 INVITED
Universality of scaling laws in correlation between velocity and shear stress in turbulent boundary layers
In this study, we analyse simultaneous measurements (at 50 Hz) of velocity at several heights and shear stress at the surface made during the Utah field campaign for the presence of ranges of scales, where distinct scale-to-scale interactions between velocity and shear stress can be identified. We find that our results are similar to those obtained in a previous study [Venugopal et al., 2003] (contrary to the claim in V2003, that the scaling relations might be dependent on Reynolds number) where wind tunnel measurements of velocity and shear stress were analysed. We use a wavelet-based scale-to-scale cross-correlation to detect three ranges of scales of interaction between velocity and shear stress, namely, (a) inertial subrange, where the correlation is negligible; (b) energy production range, where the correlation follows a logarithmic law; and (c) for scales larger than the boundary layer height, the correlation reaches a plateau.
NG54A-05
Isotropic turbulence, stable layers: facts or fictions?
Using state of the art drop sonde data (from 237 sondes over the Pacific) we examine two classical and fundamental idealizations of atmospheric science showing that they are untenable in the light of the vertical structure. The first is the notion of stable atmospheric layers. This is used for understanding atmospheric dynamics and thermodynamics, including the most advanced dynamical meteorological notions such as potential vorticity. Using the drop sonde data, we show that each apparently stable layer is actually composed of a hierarchy of unstable layers themselves with embedded stable sublayers, each with unstable sub-sub layers etc. i.e. in a Russian doll-like fractal hierarchy whose dimension we estimate. We therefore argue that the notion is untenable and must be replaced by modern scaling notions. The second idealization we examine is the turbulence assumption of isotropy. If we include intermittency, Kolmorogov's landmark proposal that fully developed turbulence has an "inertial subrange" with isotropic energy spectrum E(k)=k**-beta with beta=5/3 has apparently been spectacularly confirmed in both the horizontal direction and in the time domain (k is a wavenumber). For gradients over a horizontal distance deltax this implies deltav=deltaz**Hh (Hh=1/3 corresponds to beta=5/3). Remarkably, Hv for gradients over vertical distances deltaz (deltav=deltaz**Hv) has not been seriously investigated. Using drop sonde data of horizontal wind, we find that from scales of 5 m to 10 km from the surface layer through to the top of the troposphere, Hv is close to (or larger) than the Bolgiano-Obukhov value 3/5. Hv greater than Hh implies that a) the atmosphere becomes progressively less stratified at smaller scales although in a scaling way; b) that at most a single (roughly) isotropic "sphero- scale" exists (often in the range 1-100 cm).
NG54A-06
Detection of Intermittent Turbulence in Stable Boundary Layer Using Empirical Mode Decomposition
Detecting and characterizing intermittent turbulence in stable boundary layer is important for both understanding the meteorological processes and for structural damage mitigation. Since such intermittent turbulence events are often short in duration with high amplitudes, traditional stationary or linear signal processing often fail to catch the physical phenomena. Our analysis seeks these localized phenomena with the empirical mode decomposition (EMD) method. EMD has recently gained more and more popularity for analyzing nonlinear and non-stationary signals. In particular, the method extracts concentrated structures without leaving the time domain, making event identification possible. In this research, we first apply EMD method to the data to extract the so- called intrinsic mode functions (IMF) in the time domain. During this filtering process, our first several IMFs will contain the shortest oscillations of the data with high amplitudes. Thus, the potential intermittent turbulent events embedded in the data can be identified. To further characterize the intermittence, a rigorous statistical test, based on the oldest methods in nonparametric statistics, the development of a randomized reference distribution is explored. Based on this statistical test, a threshold is defined to provide information in the data that is statistically significant, in our case, the intermittent turbulence events. An extensive collection of field observation data from various campaigns is used to corroborate the potential of our coherent structure detection methodology.
NG54A-07
Multiple Steady States Versus Optimality in the Atmosphere-Biosphere System
Multiple steady states (MSS) can emerge from complex system dynamics as a result of interactions and positive feedbacks. As a result of MSS, the emergent state of the system depends on the initial conditions. An example for MSS is the interaction of vegetation with precipitation, where more vegetation cover enhances atmospheric moisture recycling, thereby enhancing vegetation cover in water-limited regions. One alternative view is that vegetation is optimally adapted to its environment, thereby maximizing its dissipative activity (which is consistent with the principle of Maximum Entropy Production, MEP). We used a coupled vegetation-climate model of intermediate complexity and conducted simulations that compare these two approaches. To demonstrate the concept of MSS, we conducted simulations with prescribed biomass and precipitation levels and found that the model in most cases only yields one steady state. We then performed additional sensitivity simulations to vegetation form and function to demonstrate that there is a range of possible steady states that differ in their associated vegetation productivity. From these results we conclude that it is more appropriate to view the atmosphere-biosphere system as a complex dissipative system with many degrees of freedom with many possible steady states in which optimization can take place rather than a system that operates merely within a few steady state solutions.
NG54A-08
Turbulent scaling in the atmosphere and its meteorological implications
We present an evaluation of the predictive capability of the structure function of turbulent velocity fluctuations in the lower atmospheric boundary layer in terms of the occurrence of a convective storm at the location of estimation, in a tropical climate. The importance of the same-day predictive capability of the structure of turbulence relies on the fact that, during the rainy season, tropical storms develop in a matter of less than an hour. Results from data obtained during the TRMM-LBA project at a site in Rondonia, Brazil, are being presented, and an explanatory hypothesis is being formulated.