A primary focus of coastal science during the past 3 decades has been the question: How does anthropogenic nutrient enrichment cause change in the structure or function of nearshore coastal ecosystems? This theme of environmental science is recent, so our conceptual model of the coastal eutrophication problem continues to change rapidly In this review, I suggest that the early (Phase I) con- ceptual model was strongly influenced by limnologists, who began intense study of lake eutrophication by the 1960s The Phase I model emphasized changing nutrient input as a signal, and responses to that signal as increased phytoplankton biomass and primary production, decomposition of phytoplankton- derived organic matter, and enhanced depletion of oxygen from bottom waters Coastal research in recent decades has identified key differences in the responses of lakes and coastal-estuarine ecosystems to nutrient enrichment The contemporary (Phase II) conceptual model reflects those differences and includes explicit recognition of (1) system-specific attributes that act as a filter to modulate the responses to enrichment (leading to large differences among estuarine-coastal systems in their sensitivity to nu- trient enrichment); and (2) a complex suite of direct and indirect responses including linked changes in: water transparency, distribution of vascular plants and biomass of macroalgae, sediment biogeochem- istry and nutrient cycling, nutrient ratios and their regulation of phytoplankton community composition, frequency of toxic/harmful algal blooms, habitat quality for metazoans, reproduction/growth/survival of pelagic and benthic invertebrates, and subtle changes such as shifts in the seasonality of ecosystem functions Each aspect of the Phase II model is illustrated here with examples from coastal ecosystems around the world In the last section of this review I present one vision of the next (Phase III) stage in the evolution of our conceptual model, organized around 5 questions that will guide coastal science in the early 21st century: (1) How do system-specific attributes constrain or amplify the responses of coastal ecosystems to nutrient enrichment? (2) How does nutrient enrichment interact with other stressors (toxic contaminants, fishing harvest, aquaculture, nonindigenous species, habitat loss, climate change, hydro- logic manipulations) to change coastal ecosystems? (3) How are responses to multiple stressors linked? (4) How does human-induced change in the coastal zone impact the Earth system as habitat for humanity and other species? (5) How can a deeper scientific understanding of the coastal eutrophication problem be applied to develop tools for building strategies at ecosystem restoration or rehabilitation?

https://www.int-res.com/articles/meps/210/m210p223.pdf

Our evolving conceptual model of the coastal eutrophication problem

The sensitivity of sonic anemometer-derived stress estimates to the tilt of the anemometer is investigated. The largest stress errors are shown to occur for unstable stratification (z/L<0) and deep convective boundary layers. Three methods for determining the tilt angles relative to a mean streamline coordinate system and for computing the tilt-corrected stresses are then compared. The most commonly used method, involving a double rotation of the anemometers' axes, is shown to result in significant run-to-run stress errors due to the sampling uncertainty of the mean vertical velocity. An alternative method, requiring a triple rotation of the anemometer axes, is shown to result in even greater run-to-run stress errors due to the combined sampling errors of the mean vertical velocity and the cross-wind stress. For measurements over the sea where the cross-stream stress is important, the double rotation method is shown to overestimate the surface stress, due to the uncorrected lateral tilt component. A third method, using a planar fit technique, isshown to reduce the run-to-run stress errors due to sampling effects, and provides an unbiased estimate of the lateral stress.

Sonic anemometer tilt correction algorithms

The limits to growth

Global review and synthesis of trends in observed terrestrial near-surface wind speeds; implications for evaporation

Wavelet transforms originated in geophysics in the early 1980s for the analysis of seismic signals. Since then, significant mathematical advances in wavelet theory have enabled a suite of applications in diverse fields. In geophysics the power of wavelets for analysis of nonstationary processes that contain multiscale features, detection of singularities, analysis of transient phenom- ena, fractal and multifractal processes, and signal com- pression is now being exploited for the study of several processes including space-time precipitation, remotely sensed hydrologic fluxes, atmospheric turbulence, can- opy cover, land surface topography, seafloor bathymetry, and ocean wind waves. It is anticipated that in the near future, significant further advances in understanding and modeling geophysical processes will result from the use of wavelet analysis. In this paper we review the basic properties of wavelets that make them such an attractive and powerful tool for geophysical applications. We dis- cuss continuous, discrete, orthogonal wavelets and wavelet packets and present applications to geophysical processes.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97RG00427

Wavelet analysis for geophysical applications

Wind-induced vibration of high-rise building with tuned mass damper including soil–structure interaction

(Received 26 May 1993; accepted 8 March 1994) Orthonormal wavelet expansions are applied to atmospheric surface layer velocity and temperature measurements above a uniform bare soil ‘ surface that exhibit a long inertial subrange energy spectrum. In order to investigate intermittency effects on Kolmogorov’ s theory, a direct relation between the &h-order structure function and the wavelet coefficients is derived. This relation is used to examine deviations from the classical Kolmogorov theory for velocity and temperature in the inertial subrange. The local nature of the orthonormal wavelet transform in physical space aided the identification of events directly contributing to intermittency buildup at inertial subrange scales. These events occur at edges of large eddies and contaminate the Kolmogorov inertial subrange scaling. By suppressing these events, the statistical structure of the inertial subrange for the velocity and temperature, as described by Kolmogorov’ s theory, is recovered. The suppression of intermittency on the nth-order structure function is carried out via a conditional wavelet sampling scheme. The conditioned wavelet statistics reproduced the Kolmogorov scaling (up to n = 6) in the inertial subrange and result in a zero intermittency factor. The conditional wavelet statistics for the mixed velocity temperature structure functions are also presented. It was found that the conditional wavelet statistics for these mixed moments result in a thermal intermittency parameter consistent with other laboratory and field measurements. The relationship between Kolmogorov’ s theory and near-Gaussian statistics for velocity and temperature gradients is also considered. 1. INTRODUCTION From Kolmogorov’ theory (K41), the ensemble average of the nth order velocity difference (Auij between two points separated by spatial distance (Y), in the inertial sub- range, can be computed using (~hz#)=K,((~))~‘ ~r~‘ ~, (1) where E is the turbulent energy dissipation rate

/pdf/intermittency-local-isotropy-and-non-gaussian-statistics-in-32t02drs2d.pdf

Intermittency, local isotropy, and non‐Gaussian statistics in atmospheric surface layer turbulence

The existence of universal power laws at low wavenumbers (K) in the energy spectrum (Eu) of the turbulent longitudinal velocity (u) is examined theoretically and experimentally for the near-neutral atmospheric surface layer. Newly derived power-law solutions to Tchen's approximate integral spectral budget equation are tested for strong- and weak-interaction cases between the mean flow and turbulent vorticity fields. To verify whether these solutions reproduce the measured Eu at low wavenumbers, velocity measurements were collected in the dynamic sublayer of the atmosphere at three sites and in the inner region of a laboratory open channel. The atmospheric surface layer measurements were carried out using triaxial sonic anemometers over tall corn, short grass, and smooth desert-like sandy soil. The open channel measurements were performed using a two-dimensional boundary-layer probe above a smooth stainless steel bed. Comparisons between the proposed analytical solution for Eu, the dimensional analysis by Kader and Yaglom, and the measured Haar wavelet Eu spectra are presented. It is shown that when strong interaction between the mean flow and turbulent vorticity field occurs, wavelet spectra measurements, predictions by the analytical solution, and predictions by the dimensional analysis of Kader-Yaglom (KY) are all in good agreement and confirm the existence of a -1 power law in Eu(= Cuuu2* K-1, where Cuu is a constant and u* is the friction velocity). The normalized upper wavenumber limit of the -1 power law (Kz = 1, where z is the height above the zero-plane displacement) is estimated using two separate approaches and compared to the open channel and atmospheric surface-layer measurements. It is demonstrated that the measured upper wavenumber limit is consistent with Tchen's budget but not with the KY assumptions. The constraints as to whether the mean flow and turbulent vorticity strongly interact are considered using a proposed analysis by Panchev. It is demonstrated that the arguments by Panchev cannot be consistent with surface-layer turbulence. Using dimensional analysis and Heisenberg's turbulent viscosity model, new constraints are proposed. The new constraints agree with the open channel and atmospheric surface-layer measurements, Townsend's ‘inactive eddy motion hypothesis’, and the Perry et al. analysis.

A theoretical and experimental investigation of energy-containing scales in the dynamic sublayer of boundary-layer flows

Numerical simulation of two trains intersecting in a tunnel

The probability density functions (pdf's) for the longitudinal and vertical velocities, temperature, their derivatives, and momentum and sensible heatfluxes were measured in the atmospheric surface layer for a wide range of atmospheric stability conditions. The measured pdf's for both the velocity and the temperaturefluctuations are near-Gaussian and consistent with corresponding laboratory measurements for near- neutral and stable stability conditions. Hence thefirst- and second-order moments are sufficient to predict the heat and momentumflux pdf's. The lower-order moments can be estimated from mean meteorological conditions using surface layer similarity theory. For unstable conditions the pdf for temperature is non-Gaussian and is strongly skewed due to local convective thermal plumes. For near-neutral and stable conditions the pdf's for the velocity and temperature longitudinal gradients have long exponential tails, in agreement withfindings in laboratory experiments and numerical simulations.

/pdf/probability-density-functions-of-turbulent-velocity-and-4kdpna9wp9.pdf

Chia Ren Chu

Papers

Wind-induced vibration of high-rise building with tuned mass damper including soil–structure interaction

Intermittency, local isotropy, and non‐Gaussian statistics in atmospheric surface layer turbulence

A theoretical and experimental investigation of energy-containing scales in the dynamic sublayer of boundary-layer flows

Numerical simulation of two trains intersecting in a tunnel

Probability density functions of turbulent velocity and temperature in the atmospheric surface layer