Horizontal Grid Size Selection and its Influence on Mesoscale Model Simulations

The use of two-dimensional spectral analysis applied to terrain heights in order to determine characteristic terrain spatial scales and its subsequent use for the objective definition of an adequate grid size required to resolve terrain forcing are presented in this paper. In order to illustrate the influence of grid size, atmospheric flow in a complex terrain area of the Spanish east coast is simulated by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical model using different horizontal grid resolutions. In this area, a grid size of 2 km is required to account for 95% of terrain variance. Comparison among results of the different simulations shows that, although the main wind behavior does not change dramatically, some small-scale features appear when using a resolution of 2 km or finer. Horizontal flow pattern differences are significant both in the nighttime, when terrain forcing is more relevant, and in the daytime, when thermal forcing is dominant. Vertical structures also are investigated, and results show that vertical advection is influenced highly by the horizontal grid size during the daytime period. The turbulent kinetic energy and potential temperature vertical cross sections show substantial differences in the structure of the planetary boundary layer for each model configuration

A non-normal topology generated by a two-point selection

We construct a two-point selection f : [P](2) -> P, where P is the set of the irrational numbers, such that the space (P, tau(f)) is not normal and it is not collectionwise Hausdorff either. Here, tau(f) denotes the topology generated by the two-point selection f. This example answers a question posed by V. Gutev and T. Nogura. We also show that if f :[X](2) -> X is a two-point selection such that the topology tau(f) has countable pseudocharacter, then tau(f) is a Tychonoff topology. (C) 2008 Elsevier B.V. All rights reserved.

A Fast Algorithm for Weber Problem on a Grid

AMS subject classification: 90B80.

Poster abstract: Smart-HOP: a reliable handoff procedure for supporting mobility in wireless sensor networks

This poster abstract presents smart-HOP, a reliable handoff mechanism for mobility support in Wireless Sensor Networks (WSNs). This technique relies on a fuzzy logic approach applied at two levels: the link quality estimation level and the access point selection level. We present the conceptual design of smart-HOP and then we discuss implementation requirements and challenges.

Assessment of the ensembles regional climate models in the representation of precipitation variability and extremes over Portugal

A new data set of daily gridded observations of precipitation, computed from over 400 stations in Portugal, is used to assess the performance of 12 regional climate models at 25 km resolution, from the ENSEMBLES set, all forced by ERA-40 boundary conditions, for the 1961-2000 period. Standard point error statistics, calculated from grid point and basin aggregated data, and precipitation related climate indices are used to analyze the performance of the different models in representing the main spatial and temporal features of the regional climate, and its extreme events. As a whole, the ENSEMBLES models are found to achieve a good representation of those features, with good spatial correlations with observations. There is a small but relevant negative bias in precipitation, especially in the driest months, leading to systematic errors in related climate indices. The underprediction of precipitation occurs in most percentiles, although this deficiency is partially corrected at the basin level. Interestingly, some of the conclusions concerning the performance of the models are different of what has been found for the contiguous territory of Spain; in particular, ENSEMBLES models appear too dry over Portugal and too wet over Spain. Finally, models behave quite differently in the simulation of some important aspects of local climate, from the mean climatology to high precipitation regimes in localized mountain ranges and in the subsequent drier regions.

A generalized 1D particle transport method for convection diffusion reaction model

This work is devoted to the development of numerical method to deal with convection diffusion dominated problem with reaction term, non - stiff chemical reaction and stiff chemical reaction. The technique is based on the unifying Eulerian - Lagrangian schemes (particle transport method) under the framework of operator splitting method. In the computational domain, the particle set is assigned to solve the convection reaction subproblem along the characteristic curves created by convective velocity. At each time step, convection, diffusion and reaction terms are solved separately by assuming that, each phenomenon occurs separately in a sequential fashion. Moreover, adaptivities and projection techniques are used to add particles in the regions of high gradients (steep fronts) and discontinuities and transfer a solution from particle set onto grid point respectively. The numerical results show that, the particle transport method has improved the solutions of CDR problems. Nevertheless, the method is time consumer when compared with other classical technique e.g., method of lines. Apart from this advantage, the particle transport method can be used to simulate problems that involve movingsteep/smooth fronts such as separation of two or more elements in the system.

Flächenhafte und funktionale Analyse kleinräumiger standortbedingter Variationen der Grünlandvegetation und -produktivität

Zur Abbildung heterogener Standorteigenschaften und Ertragspotenziale werden zunehmend flächenhafte Daten nachgefragt. Insbesondere für Grünland, das häufig durch ausgeprägte Standortheterogenität gekennzeichnet ist, ergeben sich hohe Anforderungen an die Wiedergabequalität, denn die realen Verhältnisse sollen in praktikabler Weise möglichst exakt abgebildet werden. Außerdem können flächenhafte Daten genutzt werden, um Zusammenhänge zwischen teilflächenspezifischen Standorteigenschaften und Grünlandaspekten detaillierter zu analysieren und bisher nicht erkannte Wechselbeziehungen nachzuweisen. Für mitteleuropäisches Grünland lagen zu Beginn dieser Arbeit derartige räumliche Untersuchungen nicht oder nur in Teilaspekten vor. Diese Arbeit befasste sich mit der Analyse von Wirkungsbeziehungen zwischen Standort- und Grünlandmerkmalen auf einer im Nordhessischen Hügelland (Deutschland) weitgehend praxisüblicher bewirtschafteten 20 ha großen Weidefläche. Erhoben wurden als Standortfaktoren die Geländemorphologie, die Bodentextur, die Grundnährstoffgehalten sowie als Parameter des Grünlandbestandes die botanische Zusammensetzung, der Ertrag und die Qualitätsparameter. Sie wurden sowohl in einem 50 m-Raster ganzflächig, als auch auf drei 50x50 m großen Teilflächen in erhöhter Beprobungsdichte (6,25 m-Rasterweite) aufgenommen. Die relevanten Fragestellungen zielen auf die räumliche und zeitliche Variabilität von Grünlandbestandesparametern innerhalb von Grünlandflächen sowie deren Abhängigkeit von den Standortfaktoren. Ein weiterer Schwerpunkt war die Überprüfung der Frage, ob die reale Variabilität der Zielvariablen durch die Interpolierung der punktuell erfassten Daten wiedergegeben werden kann. Die Beziehungen zwischen Standort- und Grünlandmerkmalen wurden mit monokausalen und multivariaten Ansätzen untersucht. Die Ergebnisse ließen, unabhängig vom Jahreseinfluss, bereits bestimmte Zusammenhänge zwischen botanischer Zusammensetzung und Standort, auch auf dem untersuchten kleinen Maßstab innerhalb der Grünlandfläche, finden. Demzufolge können unterschiedliche Areale abgegrenzt und charakterisiert werden, die als Grundlage für Empfehlungen zur Ausweisung von Arealen zur teilspezifischen Bewirtschaftung erarbeitet wurden. Die Validierung der interpolierten Daten zeigte, dass die 50-m Rasterbeprobung nur eine begrenzte Wiedergabe der räumlichen Variabilität ermöglicht. Inwieweit derartige Beziehungen quantitativ genauer beschreibbar sind, bleibt auf Grund der verbliebenen unerklärten Varianz im Datensatz dieser Studie offen.

Design and analysis of climate model experiments for the efficient estimation of anthropogenic signals

Presented herein is an experimental design that allows the effects of several radiative forcing factors on climate to be estimated as precisely as possible from a limited suite of atmosphere-only general circulation model (GCM) integrations. The forcings include the combined effect of observed changes in sea surface temperatures, sea ice extent, stratospheric (volcanic) aerosols, and solar output, plus the individual effects of several anthropogenic forcings. A single linear statistical model is used to estimate the forcing effects, each of which is represented by its global mean radiative forcing. The strong colinearity in time between the various anthropogenic forcings provides a technical problem that is overcome through the design of the experiment. This design uses every combination of anthropogenic forcing rather than having a few highly replicated ensembles, which is more commonly used in climate studies. Not only is this design highly efficient for a given number of integrations, but it also allows the estimation of (nonadditive) interactions between pairs of anthropogenic forcings. The simulated land surface air temperature changes since 1871 have been analyzed. The changes in natural and oceanic forcing, which itself contains some forcing from anthropogenic and natural influences, have the most influence. For the global mean, increasing greenhouse gases and the indirect aerosol effect had the largest anthropogenic effects. It was also found that an interaction between these two anthropogenic effects in the atmosphere-only GCM exists. This interaction is similar in magnitude to the individual effects of changing tropospheric and stratospheric ozone concentrations or to the direct (sulfate) aerosol effect. Various diagnostics are used to evaluate the fit of the statistical model. For the global mean, this shows that the land temperature response is proportional to the global mean radiative forcing, reinforcing the use of radiative forcing as a measure of climate change. The diagnostic tests also show that the linear model was suitable for analyses of land surface air temperature at each GCM grid point. Therefore, the linear model provides precise estimates of the space time signals for all forcing factors under consideration. For simulated 50-hPa temperatures, results show that tropospheric ozone increases have contributed to stratospheric cooling over the twentieth century almost as much as changes in well-mixed greenhouse gases.

Prediction of a typhoon using a fine-mesh NWP model

The ECMWF operational grid point model (with a resolution of 1.875° of latitude and longitude) and its limited area version (with a resolution of !0.47° of latitude and longitude) with boundary values from the global model have been used to study the simulation of the typhoon Tip. The fine-mesh model was capable of simulating the main structural features of the typhoon and predicting a fall in central pressure of 60 mb in 3 days. The structure of the forecast typhoon, with a warm core (maximum potential temperature anomaly 17 K). intense swirling wind (maximum 55 m s-1 at 850 mb) and spiralling precipitation patterns is characteristic of a tropical cyclone. Comparison with the lower resolution forecast shows that the horizontal resolution is a determining factor in predicting not only the structure and intensity but even the movement of these vortices. However, an accurate and refined initial analysis is considered to be a prerequisite for a correct forecast of this phenomenon.

Changing European storm loss potentials under modified climate conditions according to ensemble simulations of the ECHAM5/MPI-OM1 GMC

A simple storm loss model is applied to an ensemble of ECHAM5/MPI-OM1 GCM simulations in order to estimate changes of insured loss potentials over Europe in the 21st century. Losses are computed based on the daily maximum wind speed for each grid point. The calibration of the loss model is performed using wind data from the ERA40-Reanalysis and German loss data. The obtained annual losses for the present climate conditions (20C, three realisations) reproduce the statistical features of the historical insurance loss data for Germany. The climate change experiments correspond to the SRES-Scenarios A1B and A2, and for each of them three realisations are considered. On average, insured loss potentials increase for all analysed European regions at the end of the 21st century. Changes are largest for Germany and France, and lowest for Portugal/Spain. Additionally, the spread between the single realisations is large, ranging e.g. for Germany from −4% to +43% in terms of mean annual loss. Moreover, almost all simulations show an increasing interannual variability of storm damage. This assessment is even more pronounced if no adaptation of building structure to climate change is considered. The increased loss potentials are linked with enhanced values for the high percentiles of surface wind maxima over Western and Central Europe, which in turn are associated with an enhanced number and increased intensity of extreme cyclones over the British Isles and the North Sea.

Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)

In addition to CO2, the climate impact of aviation is strongly influenced by non-CO2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO2 emission effects are characterised by a short lifetime, their climate impact largely depends on emission location and time; that is to say, emissions in certain locations (or times) can lead to a greater climate impact (even on the global average) than the same emission in other locations (or times). Avoiding these climate-sensitive regions might thus be beneficial to climate. Here, we describe a modelling chain for investigating this climate impact mitigation option. This modelling chain forms a multi-step modelling approach, starting with the simulation of the fate of emissions released at a certain location and time (time-region grid points). This is performed with the chemistry–climate model EMAC, extended via the two submodels AIRTRAC (V1.0) and CONTRAIL (V1.0), which describe the contribution of emissions to the composition of the atmosphere and to contrail formation, respectively. The impact of emissions from the large number of time-region grid points is efficiently calculated by applying a Lagrangian scheme. EMAC also includes the calculation of radiative impacts, which are, in a second step, the input to climate metric formulas describing the global climate impact of the emission at each time-region grid point. The result of the modelling chain comprises a four-dimensional data set in space and time, which we call climate cost functions and which describes the global climate impact of an emission at each grid point and each point in time. In a third step, these climate cost functions are used in an air traffic simulator (SAAM) coupled to an emission tool (AEM) to optimise aircraft trajectories for the North Atlantic region. Here, we describe the details of this new modelling approach and show some example results. A number of sensitivity analyses are performed to motivate the settings of individual parameters. A stepwise sanity check of the results of the modelling chain is undertaken to demonstrate the plausibility of the climate cost functions.

The XWS open access catalogue of extreme European windstorms from 1979 to 2012

The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe in the period 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high-loss (severe) storms. The best-performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated. Possible reasons for this underestimation include the model failing to simulate strong enough pressure gradients and not representing convective gusts. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at www.europeanwindstorms.org.

Serial clustering of extratropical cyclones in a multi-model ensemble of historical and future simulations

This study has investigated serial (temporal) clustering of extra-tropical cyclones simulated by 17 climate models that participated in CMIP5. Clustering was estimated by calculating the dispersion (ratio of variance to mean) of 30 December-February counts of Atlantic storm tracks passing nearby each grid point. Results from single historical simulations of 1975-2005 were compared to those from historical ERA40 reanalyses from 1958-2001 ERA40 and single future model projections of 2069-2099 under the RCP4.5 climate change scenario. Models were generally able to capture the broad features in reanalyses reported previously: underdispersion/regularity (i.e. variance less than mean) in the western core of the Atlantic storm track surrounded by overdispersion/clustering (i.e. variance greater than mean) to the north and south and over western Europe. Regression of counts onto North Atlantic Oscillation (NAO) indices revealed that much of the overdispersion in the historical reanalyses and model simulations can be accounted for by NAO variability. Future changes in dispersion were generally found to be small and not consistent across models. The overdispersion statistic, for any 30 year sample, is prone to large amounts of sampling uncertainty that obscures the climate change signal. For example, the projected increase in dispersion for storm counts near London in the CNRMCM5 model is 0.1 compared to a standard deviation of 0.25. Projected changes in the mean and variance of NAO are insufficient to create changes in overdispersion that are discernible above natural sampling variations.

Mechanisms underlying temperature extremes in Iberia: a Lagrangian perspective

The mechanisms underlying the occurrence of temperature extremes in Iberia are analysed considering a Lagrangian perspective of the atmospheric flow, using 6-hourly ERA-Interim reanalysis data for the years 1979–2012. Daily 2-m minimum temperatures below the 1st percentile and 2-m maximum temperatures above the 99th percentile at each grid point over Iberia are selected separately for winter and summer. Four categories of extremes are analysed using 10-d backward trajectories initialized at the extreme temperature grid points close to the surface: winter cold (WCE) and warm extremes (WWE), and summer cold (SCE) and warm extremes (SWE). Air masses leading to temperature extremes are first transported from the North Atlantic towards Europe for all categories. While there is a clear relation to large-scale circulation patterns in winter, the Iberian thermal low is important in summer. Along the trajectories, air mass characteristics are significantly modified through adiabatic warming (air parcel descent), upper-air radiative cooling and near-surface warming (surface heat fluxes and radiation). High residence times over continental areas, such as over northern-central Europe for WCE and, to a lesser extent, over Iberia for SWE, significantly enhance these air mass modifications. Near-surface diabatic warming is particularly striking for SWE. WCE and SWE are responsible for the most extreme conditions in a given year. For WWE and SCE, strong temperature advection associated with important meridional air mass transports are the main driving mechanisms, accompanied by comparatively minor changes in the air mass properties. These results permit a better understanding of mechanisms leading to temperature extremes in Iberia.

A new method for the characterisation and verification of local spatial predictability for convective scale ensembles

The use of kilometre-scale ensembles in operational forecasting provides new challenges for forecast interpretation and evaluation to account for uncertainty on the convective scale. A new neighbourhood based method is presented for evaluating and characterising the local predictability variations from convective scale ensembles. Spatial scales over which ensemble forecasts agree (agreement scales, S^A) are calculated at each grid point ij, providing a map of the spatial agreement between forecasts. By comparing the average agreement scale obtained from ensemble member pairs (S^A(mm)_ij), with that between members and radar observations (S^A(mo)_ij), this approach allows the location-dependent spatial spread-skill relationship of the ensemble to be assessed. The properties of the agreement scales are demonstrated using an idealised experiment. To demonstrate the methods in an operational context the S^A(mm)_ij and S^A(mo)_ij are calculated for six convective cases run with the Met Office UK Ensemble Prediction System. The S^A(mm)_ij highlight predictability differences between cases, which can be linked to physical processes. Maps of S^A(mm)_ij are found to summarise the spatial predictability in a compact and physically meaningful manner that is useful for forecasting and for model interpretation. Comparison of S^A(mm)_ij and S^A(mo)_ij demonstrates the case-by-case and temporal variability of the spatial spread-skill, which can again be linked to physical processes.