The effect of the solar rotational irradiance variation on the middle and upper atmosphere calculated by a three-dimensional chemistry-climate model

This paper analyzes the effects of the solar rotational (27-day) irradiance variations on the chemical composition and temperature of the stratosphere, mesosphere and lower thermosphere as simulated by the three-dimensional chemistry-climate model HAMMONIA. Different methods are used to analyze the model results, including high resolution spectral and cross-spectral techniques. To force the simulations, an idealized irradiance variation with a constant period of 27 days (apparent solar rotation period) and with constant amplitude is used. While the calculated thermal and chemical responses are very distinct and permanent in the upper atmosphere, the responses in the stratosphere and mesosphere vary considerably in time despite the constant forcing. The responses produced by the model exhibit a non-linear behavior: in general, the response sensitivities (not amplitudes) decrease with increasing amplitude of the forcing. In the extratropics the responses are, in general, seasonally dependent with frequently stronger sensitivities in winter than in summer. Amplitude and phase lag of the ozone response in the tropical stratosphere and lower mesosphere are in satisfactory agreement with available observations. The agreement between the calculated and observed temperature response is generally worse than in the case of ozone

Localness of energy cascade in hydrodynamic turbulence, I. Smooth coarse-graining

We introduce a novel approach to scale-decomposition of the fluid kinetic energy (or other quadratic integrals) into band-pass contributions from a series of length-scales. Our decomposition is based on a multiscale generalization of the ``Germano identity'' for smooth, graded filter kernels. We employ this method to derive a budget equation that describes the transfers of turbulent kinetic energy both in space and in scale. It is shown that the inter-scale energy transfer is dominated by local triadic interactions, assuming only the scaling properties expected in a turbulent inertial-range. We derive rigorous upper bounds on the contributions of non-local triads, extending the work of Eyink (2005) for low-pass filtering. We also propose a physical explanation of the differing exponents for our rigorous upper bounds and for the scaling predictions of Kraichnan (1966,1971). The faster decay predicted by Kraichnan is argued to be the consequence of additional cancellations in the signed contributions to transfer from non-local triads, after averaging over space. This picture is supported by data from a $512^3$ pseudospectral simulation of Navier-Stokes turbulence with phase-shift dealiasing.Comment: 26 pages, 4 figure

Ozone Response to Aircraft Emissions: Sensitivity Studies with Two-dimensional Models

Our first intercomparison/assessment of the effects of a proposed high-speed civil transport (HSCT) fleet on the stratosphere is presented. These model calculations should be considered more as sensitivity studies, primarily designed to serve the following purposes: (1) to allow for intercomparison of model predictions; (2) to focus on the range of fleet operations and engine specifications giving minimal environmental impact; and (3) to provide the basis for future assessment studies. The basic scenarios were chosen to be as realistic as possible, using the information available on anticipated developments in technology. They are not to be interpreted as a commitment or goal for environmental acceptability

Physical Response of the York River Estuary to Hurricane Isabel

After making landfall on the North Carolina coast on the morning of 18 September 2003, Category 2 Hurricane Isabel tracked northward parallel to and slightly west of the Chesapeake Bay. At Gloucester Point, near the mouth of the York River estuary, strong onshore winds with speeds in excess of 20 m⋅s-1 persisted for over 12 hours and peak winds reached over 40 m⋅s-1, causing a sustained up-estuary wind stress. Storm surge exceeded 2 m throughout most of the lower Chesapeake Bay. A 600 kHz acoustic Doppler current profiler (ADCP), deployed at a depth of 8.5 m off Gloucester Point, provided high-quality data on waves, storm surge, currents, and acoustic backscatter throughout the water column before, during, and after the storm. Pressure and salinity sensors at three additional sites further up the estuary provided information on water surface slope and saltwater excursion up the estuary. A first-order estimate of three terms of the along-channel momentum equation (barotropic pressure gradient, acceleration, and friction) showed that the pressure gradient appeared to be balanced by the wind stress and the acceleration during the storm. The storm’s path and slow speed were the primary causes of the extremely high storm surge relative to past storms in the area.https://scholarworks.wm.edu/vimsbooks/1001/thumbnail.jp

Localness of energy cascade in hydrodynamic turbulence, II. Sharp spectral filter

We investigate the scale-locality of subgrid-scale (SGS) energy flux and inter-band energy transfers defined by the sharp spectral filter. We show by rigorous bounds, physical arguments and numerical simulations that the spectral SGS flux is dominated by local triadic interactions in an extended turbulent inertial-range. Inter-band energy transfers are also shown to be dominated by local triads if the spectral bands have constant width on a logarithmic scale. We disprove in particular an alternative picture of ``local transfer by nonlocal triads,'' with the advecting wavenumber mode at the energy peak. Although such triads have the largest transfer rates of all {\it individual} wavenumber triads, we show rigorously that, due to their restricted number, they make an asymptotically negligible contribution to energy flux and log-banded energy transfers at high wavenumbers in the inertial-range. We show that it is only the aggregate effect of a geometrically increasing number of local wavenumber triads which can sustain an energy cascade to small scales. Furthermore, non-local triads are argued to contribute even less to the space-average energy flux than is implied by our rigorous bounds, because of additional cancellations from scale-decorrelation effects. We can thus recover the -4/3 scaling of nonlocal contributions to spectral energy flux predicted by Kraichnan's ALHDIA and TFM closures. We support our results with numerical data from a $512^3$ pseudospectral simulation of isotropic turbulence with phase-shift dealiasing. We conclude that the sharp spectral filter has a firm theoretical basis for use in large-eddy simulation (LES) modeling of turbulent flows.Comment: 42 pages, 9 figure

Variations in the predicted spatial distribution of atmospheric nitrogen deposition and their impact on carbon uptake by terrestrial ecosystems

Widespread mobilization of nitrogen into the atmosphere from industry, agriculture, and biomass burning and its subsequent deposition have the potential to alleviate nitrogen limitation of productivity in terrestrial ecosystems, and may contribute to enhanced terrestrial carbon uptake. To evaluate the importance of the spatial distribution of nitrogen deposition for carbon uptake and to better quantify its magnitude and uncertainty NOy-N deposition fields from five different three-dimensional chemical models, GCTM, GRANTOUR, IMAGES, MOGUNTIA, and ECHAM were used to drive NDEP, a perturbation model of terrestrial carbon uptake. Differences in atmospheric sources of NOx-N, transport, resolution, and representation of chemistry, contribute to the distinct spatial patterns of nitrogen deposition on the global land surface; these differences lead to distinct patterns of carbon uptake that vary between 0.7 and 1.3 Gt C yr−1 globally. Less than 10% of the nitrogen was deposited on forests which were most able to respond with increased carbon storage because of the wide C:N ratio of wood as well as its long lifetime. Addition of NHx-N to NOy-N deposition, increased global terrestrial carbon storage to between 1.5 and 2.0 Gt C yr−1, while the “missing terrestrial sink” is quite similar in magnitude. Thus global air pollution appears to be an important influence on the global carbon cycle. If N fertilization of the terrestrial biosphere accounts for the “missing” C sink or a substantial portion of it, we would expect significant reductions in its magnitude over the next century as terrestrial ecosystems become N saturated and O3 pollution expands

Report of the 1988 2-D Intercomparison Workshop, chapter 3

Several factors contribute to the errors encountered. With the exception of the line-by-line model, all of the models employ simplifying assumptions that place fundamental limits on their accuracy and range of validity. For example, all 2-D modeling groups use the diffusivity factor approximation. This approximation produces little error in tropospheric H2O and CO2 cooling rates, but can produce significant errors in CO2 and O3 cooling rates at the stratopause. All models suffer from fundamental uncertainties in shapes and strengths of spectral lines. Thermal flux algorithms being used in 2-D tracer tranport models produce cooling rates that differ by as much as 40 percent for the same input model atmosphere. Disagreements of this magnitude are important since the thermal cooling rates must be subtracted from the almost-equal solar heating rates to derive the net radiative heating rates and the 2-D model diabatic circulation. For much of the annual cycle, the net radiative heating rates are comparable in magnitude to the cooling rate differences described. Many of the models underestimate the cooling rates in the middle and lower stratosphere. The consequences of these errors for the net heating rates and the diabatic circulation will depend on their meridional structure, which was not tested here. Other models underestimate the cooling near 1 mbar. Suchs errors pose potential problems for future interactive ozone assessment studies, since they could produce artificially-high temperatures and increased O3 destruction at these levels. These concerns suggest that a great deal of work is needed to improve the performance of thermal cooling rate algorithms used in the 2-D tracer transport models

Stratospheric processes: Observations and interpretation

Explaining the observed ozone trends discussed in an earlier update and predicting future trends requires an understanding of the stratospheric processes that affect ozone. Stratospheric processes occur on both large and small spatial scales and over both long and short periods of time. Because these diverse processes interact with each other, only in rare cases can individual processes be studied by direct observation. Generally the cause and effect relationships for ozone changes were established by comparisons between observations and model simulations. Increasingly, these comparisons rely on the developing, observed relationships among trace gases and dynamical quantities to initialize and constrain the simulations. The goal of this discussion of stratospheric processes is to describe the causes for the observed ozone trends as they are currently understood. At present, we understand with considerable confidence the stratospheric processes responsible for the Antarctic ozone hole but are only beginning to understand the causes of the ozone trends at middle latitudes. Even though the causes of the ozone trends at middle latitudes were not clearly determined, it is likely that they, just as those over Antarctica, involved chlorine and bromine chemistry that was enhanced by heterogeneous processes. This discussion generally presents only an update of the observations that have occurred for stratospheric processes since the last assessment (World Meteorological Organization (WMO), 1990), and is not a complete review of all the new information about stratospheric processes. It begins with an update of the previous assessment of polar stratospheres (WMO, 1990), followed by a discussion on the possible causes for the ozone trends at middle latitudes and on the effects of bromine and of volcanoes

Counting using deep learning regression gives value to ecological surveys

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, which opens opportunities to automatise counting tasks. In this study, we use machine learning to automate counting objects of interest without the need to label individual objects. By leveraging already existing image-level annotations, this approach can also give value to historical data that were collected and annotated over longer time series (typical for many ecological studies), without the aim of deep learning applications. We demonstrate deep learning regression on two fundamentally different counting tasks: (i) daily growth rings from microscopic images of fish otolith (i.e., hearing stone) and (ii) hauled out seals from highly variable aerial imagery. In the otolith images, our deep learning-based regressor yields an RMSE of 3.40 day-rings and an [Formula: see text] of 0.92. Initial performance in the seal images is lower (RMSE of 23.46 seals and [Formula: see text] of 0.72), which can be attributed to a lack of images with a high number of seals in the initial training set, compared to the test set. We then show how to improve performance substantially (RMSE of 19.03 seals and [Formula: see text] of 0.77) by carefully selecting and relabelling just 100 additional training images based on initial model prediction discrepancy. The regression-based approach used here returns accurate counts ([Formula: see text] of 0.92 and 0.77 for the rings and seals, respectively), directly usable in ecological research