Lagrangian validation of numerical drifter trajectories using drifting buoys: Application to the Agulhas system

The skill of numerical Lagrangian drifter trajectories in three numerical models is assessed by comparing these numerically obtained paths to the trajectories of drifting buoys in the real ocean. The skill assessment is performed using the two-sample Kolmogorov–Smirnov statistical test. To demonstrate the assessment procedure, it is applied to three different models of the Agulhas region. The test can either be performed using crossing positions of one-dimensional sections in order to test model performance in specific locations, or using the total two-dimensional data set of trajectories. The test yields four quantities: a binary decision of model skill, a confidence level which can be used as a measure of goodness-of-fit of the model, a test statistic which can be used to determine the sensitivity of the confidence level, and cumulative distribution functions that aid in the qualitative analysis. The ordering of models by their confidence levels is the same as the ordering based on the qualitative analysis, which suggests that the method is suited for model validation. Only one of the three models, a 1/10° two-way nested regional ocean model, might have skill in the Agulhas region. The other two models, a 1/2° global model and a 1/8° assimilative model, might have skill only on some sections in the region

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.

Measurement of propagation constant in waveguides with wideband coherent terahertz spectroscopy

A quasi-optical technique for characterizing micromachined waveguides is demonstrated with wideband time-resolved terahertz spectroscopy. A transfer-function representation is adopted for the description of the relation between the signals in the input and output port of the waveguides. The time-domain responses were discretized, and the waveguide transfer function was obtained through a parametric approach in the z domain after describing the system with an autoregressive with exogenous input model. The a priori assumption of the number of modes propagating in the structure was inferred from comparisons of the theoretical with the measured characteristic impedance as well as with parsimony arguments. Measurements for a precision WR-8 waveguide-adjustable short as well as for G-band reduced-height micromachined waveguides are presented. (C) 2003 Optical Society of America.

Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom Prescribed intercomparison study

Simulated multi-model “diversity” in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated “host-model uncertainties” are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is −4.47Wm−2 and the inter-model standard deviation is 0.55Wm−2, corresponding to a relative standard deviation of 12 %. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04Wm−2, and the standard deviation increases to 1.01W−2, corresponding to a significant relative standard deviation of 97 %. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45Wm−2 (8 %) clear-sky and 0.62Wm−2 (11 %) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the Aero- Com Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11Wm−2 in the AeroCom Direct Radiative Effect experiment.

The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: a model study

The Arctic sea ice cover is thinning and retreating, causing changes in surface roughness that in turn modify the momentum flux from the atmosphere through the ice into the ocean. New model simulations comprising variable sea ice drag coefficients for both the air and water interface demonstrate that the heterogeneity in sea ice surface roughness significantly impacts the spatial distribution and trends of ocean surface stress during the last decades. Simulations with constant sea ice drag coefficients as used in most climate models show an increase in annual mean ocean surface stress (0.003 N/m2 per decade, 4.6%) due to the reduction of ice thickness leading to a weakening of the ice and accelerated ice drift. In contrast, with variable drag coefficients our simulations show annual mean ocean surface stress is declining at a rate of -0.002 N/m2 per decade (3.1%) over the period 1980-2013 because of a significant reduction in surface roughness associated with an increasingly thinner and younger sea ice cover. The effectiveness of sea ice in transferring momentum does not only depend on its resistive strength against the wind forcing but is also set by its top and bottom surface roughness varying with ice types and ice conditions. This reveals the need to account for sea ice surface roughness variations in climate simulations in order to correctly represent the implications of sea ice loss under global warming.

Using data insertion with the NAME model to simulate the 8 May 2010 Eyjafjallajökull volcanic ash cloud

A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

1,8-cineol potentiates IRF3-mediated antiviral response in human stem cells and an ex vivo model of rhinosinusitis

Common cold is one of the most frequent human inflammatory diseases caused by viruses and can facilitate bacterial super-infections resulting in sinusitis or pneumonia. The active ingredient of the drug Soledum, 1,8-cineole, is commonly applied for treating inflammatory diseases of the respiratory tract. However, the potential of 1,8-cineole for treating primary viral infections of the respiratory tract remains unclear. In the present study, we demonstrate for the first time that 1,8-cineole potentiates Poly(I:C)-induced activity of the anti-viral transcription factor Interferon Regulatory Factor 3, while simultaneously reducing pro-inflammatory NF-κB-activity in human cell lines, inferior turbinate stem cells (ITSCs) and ex vivo cultivated human nasal mucosa. Co-treatment of cell lines with Poly(I:C) and 1,8-cineole resulted in significantly increased IRF3 reporter gene activity compared to Poly(I:C) alone, whereas NF-κB-activity was reduced. Accordingly, 1,8-cineole- and Poly(I:C)-treatment led to increased nuclear translocation of IRF3 in ITSCs and a human ex vivo model of rhinosinusitis compared to the Poly(I:C)-treated approach. Nuclear translocation of IRF3 was significantly increased in ITSCs and slice cultures treated with LPS and 1,8-cineole compared to the LPS-treated cells mimicking bacterial infection. Our findings strongly suggest that 1,8-cineole potentiates the antiviral activity of IRF3 in addition to its inhibitory effect on pro-inflammatory NF-κB-signalling and may thus broaden its field of application.

The counter-propagating Rossby-wave perspective on baroclinic instability. II: Application to the Charney model

The constant-density Charney model describes the simplest unstable basic state with a planetary-vorticity gradient, which is uniform and positive, and baroclinicity that is manifest as a negative contribution to the potential-vorticity (PV) gradient at the ground and positive vertical wind shear. Together, these ingredients satisfy the necessary conditions for baroclinic instability. In Part I it was shown how baroclinic growth on a general zonal basic state can be viewed as the interaction of pairs of ‘counter-propagating Rossby waves’ (CRWs) that can be constructed from a growing normal mode and its decaying complex conjugate. In this paper the normal-mode solutions for the Charney model are studied from the CRW perspective. Clear parallels can be drawn between the most unstable modes of the Charney model and the Eady model, in which the CRWs can be derived independently of the normal modes. However, the dispersion curves for the two models are very different; the Eady model has a short-wave cut-off, while the Charney model is unstable at short wavelengths. Beyond its maximum growth rate the Charney model has a neutral point at finite wavelength (r=1). Thereafter follows a succession of unstable branches, each with weaker growth than the last, separated by neutral points at integer r—the so-called ‘Green branches’. A separate branch of westward-propagating neutral modes also originates from each neutral point. By approximating the lower CRW as a Rossby edge wave and the upper CRW structure as a single PV peak with a spread proportional to the Rossby scale height, the main features of the ‘Charney branch’ (0model where the positive PV gradient exists only at the tropopause

Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations

Climate model simulations consistently show that in response to greenhouse gas forcing surface temperatures over land increase more rapidly than over sea. The enhanced warming over land is not simply a transient effect, since it is also present in equilibrium conditions. We examine 20 models from the IPCC AR4 database. The global land/sea warming ratio varies in the range 1.36–1.84, independent of global mean temperature change. In the presence of increasing radiative forcing, the warming ratio for a single model is fairly constant in time, implying that the land/sea temperature difference increases with time. The warming ratio varies with latitude, with a minimum in equatorial latitudes, and maxima in the subtropics. A simple explanation for these findings is provided, and comparisons are made with observations. For the low-latitude (40°S–40°N) mean, the models suggest a warming ratio of 1.51 ± 0.13, while recent observations suggest a ratio of 1.54 ± 0.09.

Evaluation of the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data

Simulations of the top-of-atmosphere radiative-energy budget from the Met Office global numerical weather-prediction model are evaluated using new data from the Geostationary Earth Radiation Budget (GERB) instrument on board the Meteosat-8 satellite. Systematic discrepancies between the model simulations and GERB measurements greater than 20 Wm-2 in outgoing long-wave radiation (OLR) and greater than 60 Wm-2 in reflected short-wave radiation (RSR) are identified over the period April-September 2006 using 12 UTC data. Convective cloud over equatorial Africa is spatially less organized and less reflective than in the GERB data. This bias depends strongly on convective-cloud cover, which is highly sensitive to changes in the model convective parametrization. Underestimates in model OLR over the Gulf of Guinea coincide with unrealistic southerly cloud outflow from convective centres to the north. Large overestimates in model RSR over the subtropical ocean, greater than 50 Wm-2 at 12 UTC, are explained by unrealistic radiative properties of low-level cloud relating to overestimation of cloud liquid water compared with independent satellite measurements. The results of this analysis contribute to the development and improvement of parametrizations in the global forecast model.

A high-order arbitrarily unstructured finite-volume model of the global atmosphere: tests solving the shallow-water equations

Simulations of the global atmosphere for weather and climate forecasting require fast and accurate solutions and so operational models use high-order finite differences on regular structured grids. This precludes the use of local refinement; techniques allowing local refinement are either expensive (eg. high-order finite element techniques) or have reduced accuracy at changes in resolution (eg. unstructured finite-volume with linear differencing). We present solutions of the shallow-water equations for westerly flow over a mid-latitude mountain from a finite-volume model written using OpenFOAM. A second/third-order accurate differencing scheme is applied on arbitrarily unstructured meshes made up of various shapes and refinement patterns. The results are as accurate as equivalent resolution spectral methods. Using lower order differencing reduces accuracy at a refinement pattern which allows errors from refinement of the mountain to accumulate and reduces the global accuracy over a 15 day simulation. We have therefore introduced a scheme which fits a 2D cubic polynomial approximately on a stencil around each cell. Using this scheme means that refinement of the mountain improves the accuracy after a 15 day simulation. This is a more severe test of local mesh refinement for global simulations than has been presented but a realistic test if these techniques are to be used operationally. These efficient, high-order schemes may make it possible for local mesh refinement to be used by weather and climate forecast models.

Tripleclouds: an efficient method for representing horizontal cloud inhomogeneity in 1D radiation schemes by using three regions at each height

Radiation schemes in general circulation models currently make a number of simplifications when accounting for clouds, one of the most important being the removal of horizontal inhomogeneity. A new scheme is presented that attempts to account for the neglected inhomogeneity by using two regions of cloud in each vertical level of the model as opposed to one. One of these regions is used to represent the optically thinner cloud in the level, and the other represents the optically thicker cloud. So, along with the clear-sky region, the scheme has three regions in each model level and is referred to as “Tripleclouds.” In addition, the scheme has the capability to represent arbitrary vertical overlap between the three regions in pairs of adjacent levels. This scheme is implemented in the Edwards–Slingo radiation code and tested on 250 h of data from 12 different days. The data are derived from cloud retrievals using radar, lidar, and a microwave radiometer at Chilbolton, southern United Kingdom. When the data are grouped into periods equivalent in size to general circulation model grid boxes, the shortwave plane-parallel albedo bias is found to be 8%, while the corresponding bias is found to be less than 1% using Tripleclouds. Similar results are found for the longwave biases. Tripleclouds is then compared to a more conventional method of accounting for inhomogeneity that multiplies optical depths by a constant scaling factor, and Tripleclouds is seen to improve on this method both in terms of top-of-atmosphere radiative flux biases and internal heating rates.