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Cyprus is located in the eastern Mediterranean, an environmentally intriguing area that is subject to complex air pollution conditions, and has to be prepared for many climatic challenges. Air quality assessment and forecasting is an essential tool in strengthening the country’s adaptation strategy, providing relevant information to sectors such as agriculture and tourism, helping reduce health related financial and human life costs, as well as establishing a core national priority axis for knowledge outreach to neighbouring countries. The use of current and next generation satellite information can open a new area in operational forecasting and scientific assessment of air quality and emissions in this complex region with past, current and projected societal, financial and geo-political influences. In this work we identify and elaborate on the discrepancies of emission inventories in the region and the use of satellite data for their timely update. Utilizing the EDGAR-HTAP emission inventories compiled by the Joint Research Center for the year 2010, we use a model-based methodology to update them based on satellite-derived trends. Initially we produce a model-based concentration-vertical column density (VCD) relation derived from sensitivity tests of NOx emission fluxes in the WRF-Chem regional atmospheric model. Consequently, we translate the monthly trends obtained by satellite observations for the period 2010–2015 to produce updated emission inventories. Model simulations with the current and modified emission inventory are used to assess the discrepancies derived.

Navigation based on stellar refraction refers to a method that uses large visual field star sensor to detect several stars refracted and not refracted by earth atmosphere, and then finishes autonomous navigation based on star map recognition, with merits such as simple system structure, low cost and high navigation accuracy. However, in order to achieve full-time-running high accuracy, three key technologies, namely strong background star map acquisition, refracted star extraction under strong background and atmospheric model should be solved for such method. By constructing observation policy model and detection limit model under the strong background, this paper realizes high SNR (Signal to Noise Ratio) star map acquisition under strong background through anti-blooming function of detector, and carries out theoretical analysis and outfield test; realizes recognition of dim refracted star and high-accuracy centroid positioning of refracted star under strong background via specific star pick-up algorithm, and performs outfield test on it; studies high-accuracy atmospheric model optimization method and proposes an applicable stellar refraction atmospheric model based on atmospheric refractivity change and identical with stellar refraction rule. Finally, on the basis of key technological solution study, it constructs stellar refraction navigation simulation system based on stellar refraction navigation realization approach and analyzes the influences of key error sources on navigation accuracy through simulation, so as to obtain the result that the accuracy of full-time-running navigation based on stellar refraction is superior to 1.2 km.

Increasing levels of particulate matter pollutants over the continents and associated pollution outflows have raised considerable concerns because of their potential impacts on the Pacific storm track and the regional climate. Inspired by the previous research work in our group (Zhang et al. 2007; Li et al. 2008a), which investigated the interannual trend of deep convective clouds and precipitation over the North Pacific from the observational dataset, I kept seeking the observational evidences and theoretical basis for the impacts of Asian pollution outflows on the storm track. In this study, we have derived and identified the interannual variation of Northwest Pacific storm track intensity on the basis of reanalysis datasets. Various modeling approaches have been utilized to tackle the multiscale nature of the interaction between aerosols and large-scale circulations. Seasonal (2 month) simulations using a CR-WRF model with a two-moment bulk microphysics have been conducted to examine the aerosol effects on the regional climate over the Pacific storm track. Subsequently, the anomalies of the diabatic heating rates produced by the Asian pollution outflow from the CR-WRF simulations are prescribed in the NACR Community Atmosphere Model (CAM5) as the aerosol forcing terms. Simulations of three winters using CAM5 with and without the derived aerosol forcings have been performed. In addition, the comparisons to the results from the multiscale aerosol-climate modeling framework have been conducted to further validate the responses of the Pacific storm track to the different aerosol forcings associated with elevated pollution levels.

In order to improve the prediction accuracy of LEO, it is essential to build up an accurate atmospheric model for density prediction. However, most existing atmospheric models belong to the type of semi-empirical model, thus the data sets are not of homogeneous quality and have limited geographical and temporal coverage. Since the space-borne accelerometer could measure the total non-conservative accelerations acting on LEO directly, the atmospheric drag component could be isolated with the help of the solar and earth albedo radiation pressure models, then the atmospheric density can be calculated, which provides necessary data for making evaluation and improvement of the existing atmospheric models. This paper describes the method to retrieve the upper atmospheric density from accelerometer in detail, 3 months of observations spanning from May 2013 to July 2013 are selected to do the experiment, we use the dynamical orbit determination strategy to calibrate the accelerometers, and then retrieve the air density at the altitude of GRACE Mission. The results show that prediction models cannot exhibit the density variation in high frequency, and the in situ measurements are very useful in density analysis, in addition, it is validated that atmospheric density has a positive correlation with the solar activity intensity.

Version 2 of the Grid-point Atmospheric Model of IAP LASG (GAMIL2) has been developed by upgrading the deep convection parameterization, the cumulus cloud fraction and the two moments cloud microphysical scheme, and by changing some of the large uncertain parameters. In the present study, cloud simulations by GAMIL2 were evaluated using the satellite simulator and the CAPT method (i.e., the Climate Change Prediction Program (CCPP)—Atmospheric Radiation Measurement Program (ARM) Parameterization Testbed). Here, the shortwave cloud radiative forcing (SWCF) response of atmosphere circulation to the Nino 3 sea surface temperature anomaly and the indirect aerosol effect are discussed.

In this study, improvements on the representation of moisture process in the Spectral Atmospheric Model of IAP LASG (SAMIL) are documented. We implemented the flux-form semi-Lagrangian (FFSL) scheme to accurately transfer water substances, which is a prerequisite for the subsequent introduction of the cloud microphysical scheme. The overall performance of the new model shows significant improvements over the previous version. A bulk cloud microphysical scheme was implemented to better represent the stratiform condensation process. For deep convection, the mixing process between the active cloudy part and the environment was studied with the aid of a cloud-resolving model (CRM), which led to the framework of a new parameterization scheme. Single-column model (SCM) runs show encouraging results in the simulated cumulus mass flux.

Capabilities of the Grid-point Atmospheric Model of Institute of Atmospheric Physics/National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/LASG; GAMIL) and the Spectral Atmospheric General Circulation Model of IAP/LASG (SAMIL) in simulating the Spring Persistent Rainfall (SPR) in East Asia are evaluated by the Global Precipitation Climatology Project (GPCP). Similar to that observed in the Coupled Model Intercomparison Project Phases 3 and 5 (CMIP3/CMIP5) ensembles, rainfall amount in both GAMIL and SAMIL are slightly overestimated over the SPR domain and are underestimated over the SPR center. For the spatial structure, the northeast–southwest tilted rain belt could not be effectively reproduced by GAMIL, and the main rain belt shifts to the north of its normal position in SAMIL. According to the Taylor diagram, SAMIL generally shows better performances in simulating the SPR pattern. Similar to other atmospheric general circulation models (AGCMs) employed in CMIP3/CMIP5, the thermal contrast between East Asia and the South China Sea is overestimated in SAMIL and GAMIL. The overestimated meridional thermal contrast intensifies the southerly water vapor supply and favors the northward shifting of main rain belt.

In this study, a high-resolution grid-point atmospheric model (HGAM) has been developed on the basis of the dynamical core and physical package of the Grid-point Atmospheric Model of the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics(LASG/IAP),version 2 (GAMIL2). The new model has three horizontal resolution choices of 1° × 1°, 0.5° × 0.5°, and 0.25° × 0.25°, whereas its vertical layers are the same as those of GAMIL2. A 30-year integration of the Atmospheric Model Intercomparison Project (AMIP) is completed by using the 1° × 1° version of HGAM; short-term integrations with the 0.5° × 0.5° and 0.25° × 0.25° versions are also conducted. The simulated results of precipitation by HGAM are shown as well as those by GAMIL2 for comparison. The geographical distribution of near-surface moisture by the 0.25° × 0.25° version is also given.

The LASG/IAP Aerosol Module (LIAM) was designed to investigate aerosol–climate interactions and to be coupled with the Grid-point Atmospheric Model of IAP/LASG (GAMIL). Major aerosol types including sulfate, black carbon, organic matter, sea salt, and mineral dust are considered. The aerosol mass and number concentrations are affected by the macro- and micro-scale processes considered in LIAM, including primary emissions, atmospheric chemistry, condensation, nucleation, coagulation, water uptake, and both wet and dry deposition. The modal method was employed to describe the size distribution of aerosol particles, providing a good balance between the level of mathematical detail and the computational cost. Extensive evaluation with respect to insitu measurements and satellite retrievals indicate that GAMIL-LIAM is able to capture the geographical and temporal variations of observed aerosol mass, composition, size distribution, and optical depth.

This chapter describes the model speed and model in/out (I/O) efficiency of the high-resolution atmospheric general circulation model the Finite-volume Atmospheric Model of IAP/LASG (FAMIL), investigated at the National Supercomputer Center in Tianjin, China, on its Tianhe-1A supercomputer platform. A series of three-model-day simulations were conducted with the standard Aqua-Planet Experiment (APE) project, designed within FAMIL, to obtain time stamps for the calculation of model speed, simulation cost, and model I/O efficiency. The results of the simulation demonstrate that FAMIL has remarkable scalability below 3,456 and 6,144 cores; the lowest simulation costs were found to be 1,536 and 3,456 cores for 12.5 and 6.25 km resolutions, respectively. Furthermore, FAMIL has excellent I/O scalability and efficiencies of more than 80 and 99 % on 6 and 1,536 I/Os, respectively.

Climatological high resolution coupled climate model simulations for the maritime continent have been carried out using the regional climate model (RegCM) version 3 and the finite volume coastal ocean model (FVCOM) specifically designed to resolve regions characterized by complex geometry and bathymetry. The RegCM3 boundary forcing is provided by the EMCWF-ERA40 re-analysis. FVCOM is embedded in the Global MITgcm which provides boundary forcing. The domain of the coupled regional model covers the entire South China Sea with its through-flow, the entire Indonesian archipelago with the Indonesian through-flow (ITF) and includes a large region in the western Pacific and eastern Indian oceans. The coupled model is able to provide stable and realistic climatological simulations for a specific decade of atmospheric–oceanic variables without flux correction. The major focus of this work is on oceanic properties. First, the coupled simulation is assessed against ocean-only simulations carried out under two different sets of air–sea heat fluxes. The first set, provided by the MITgcm, is proved to be grossly deficient as the heat fluxes are evaluated by a two-dimensional, zonally averaged atmosphere and the simulated SST have anomalous cold biases. Hence the MITgcm fluxes are discarded. The second set, the NCEP re-analysis heat fluxes, produces a climatological evolution of the SST with an average cold bias of ~−0.8 °C. The coupling eliminates the cold bias and the coupled SST evolution is in excellent agreement with the analogous evolution in the SODA re-analysis data. The detailed comparison of oceanic circulation properties with the International Nusantara Stratification and Transport observations shows that the coupled simulation produces the best estimate of the total ITF transport through the Makassar strait while the transports of three ocean-only simulations are all underestimated. The annual cycle of the transport is also very well reproduced. The coupling also considerably improves the vertical thermal structure of the Makassar cross section in the upper layer affected by the heat fluxes. On the other hand, the coupling is relatively ineffective in improving the precipitation fields even though the coupled simulation captures reasonably well the precipitation annual cycle at three land stations in different latitudes., Singapore. National Research Foundation (Center for Environmental Sensing and Monitoring (CENSAM)), Singapore-MIT Alliance for Research and Technology (SMART) program, National Natural Science Foundation (China) (NSFC, No. 41106003)

This chapter describes a global atmospheric model for very high resolution simulations to explicitly calculate deep convective circulations, which play key roles not only in tropical circulations but in global circulations of the atmosphere. Since the horizontal scale of upward cores of deep convection is about a few kilometers, they cannot be directly resolved by hydrostatic atmospheric general circulation models. In order to drastically enhance horizontal resolution, a new framework for global atmospheric models is required. Around a resolution with a mesh size of the orders of a few kilometers, we need to use a nonhydrostatic dynamical core instead of the hydrostatic models described in Chapters 20–23. In general, as horizontal resolution increases, grid methods become more computationally efficient than spectral methods. As preparations for this chapter, therefore, we described a nonhydrostatic scheme in Chapter 24 and icosahedral grids in Chapter 25 as a typical emaple of grid discretization method over a sphere. This chapter combinei the numerical techniques described in the previous two chapters to introduce a global nonhydrostatic model.

Climate simulation models are used for a variety of scientific problems and accuracy of the climate prognoses is mostly limited by the resolution of the models. Finer resolution results in more accurate prognoses but, at the same time, significantly increases computational complexity. This explains the increasing interest to the High Performance Computing (HPC), and GPU computations in particular, for the climate simulations. We present an efficient implementation of the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) on the multi-GPU environment. We have obtained performance results for the number of GPUs up to 320. These results were compared with the parallel CPU version and demonstrate that our GPU implementation gives 3 times higher performance over parallel CPU version. We have also developed and validated the performance model for a full-GPU implementation of the NICAM. Results show 4.5x potential acceleration over parallel CPU version. We believe that our results are general, in that in similar applications we could achieve similar speedups, and have the ability to predict its degree over CPUs.

Numerical methods for global atmospheric modeling have been widely studied in many literatures [5, 7, 9]. It is well-recognized that the global atmospheric flows can be modeled by fully compressible Euler equations with almost no approximations necessary [7]. However, due to the multi-scale nature of the global atmosphere and the high cost of computation, other simplified models have been favorably used in most community codes.

A new single-epoch ambiguity resolution for long baseline RTK, on the basis of the ionosphere-weighted model, is proposed in this paper, which is applicable to several hundred km baselines by using linear combination of the measurements, including the double-differential wide-lane combination and ionosphere-free combination carrier-phase observation equations and UofC model. By the correct ambiguity and double-differential atmosphere delay, the real-time atmosphere model was established to provide predicted value for a new risen satellite. The establishment of real-time atmosphere predicted model, estimating the relative tropospheric zenith delay and the regional ionospheric parameters, is proved to reach an acceptable accuracy. Test data from the multiple reference station GPS networks in Chongqing, consisting of 36 baselines from 40 to 350 km, were used to evaluate the performance of the proposed approach. It is showed that the proposed algorithm can reduce the effect of the ionosphere and troposphere on the network AR and the true integer ambiguity could be achieved in a short time after the establishment of the predicted atmosphere model.

Soil airflow is crucial in determining surface evaporation, which subsequently affects the atmospheric modeling. However, most land surface models (LSMs) usually ignore the airflow and only employ the diffusion-based soil water and heat transport model. In order to check how different model complexities can affect the model performance in retrieving soil moisture and soil temperature profiles, this chapter introduces three models with gradually-decreased complexities. The results show that the most complex model (i.e. coupled soil water–vapor-air-heat transport model developed in Chap.4) can perform better than other models in retrieving soil moisture when only soil moisture observation is available. For retrieving soil temperature, the medium complex model (i.e. coupled soil water–vapor-heat transport model) stands out from the three models. The simplest model (i.e. diffusion-based soil water and heat transport model) can produce assimilation estimates of soil temperature as satisfactory as the most complex model does; and, its assimilation estimate of soil moisture closely follows its simulation (e.g. open loop), which is not a proper representative of the observed truth. Nevertheless, the RMSE between its soil moisture assimilation estimates and the observation is the lowest among the three models, which may be responsible for the popular use of the diffusion-based model in the LSMs.

The knowledge on the climatology and the statistics of extreme events is of central interest for a broad range of practical applications. To obtain such information long-term and homogeneous meteorological databases are needed. However, such time series of direct observations are not always available for sufficient long period. For regions that do not have adequate historical observations or measurements are not available or lack homogeneity, the application of advanced atmospheric numerical models is often an alternative solution. In this study a sophisticated downscaling procedure that was applied to reproduce high resolution historical records of the atmospheric conditions across the Mediterranean region is presented. This was accomplished by the dynamical downscaling of the ERA-40 reanalyses with the aid of the atmospheric model of the POSEIDON weather forecasting system. The full three dimensional atmospheric fields with 6 h of temporal resolution and the surface meteorological parameters at hourly intervals were produced for a 10-year period (1995–2004). The meteorological variables are readily available at 10 km resolution and may constitute the atmospheric forcing to drive wave, ocean hydrodynamic and hydrological models, as well as the baseline data for environmental impact assessment studies.

The article introduces an automatic restoration method for images shot in foggy day. It is based on two-color atmospheric model. The method needs an image which is affected by the weather. The method also automatically calculates the brightness values of sky and the color direction of atmospheric light. Because the extraction from the sky area is more accurate and larger than the regional of the manual input, the brightness values of sky and the color direction of atmospheric light are got. They are closer to the actual values. This paper introduces this method of histogram adjustment for the restored image, and also introduces a method of adjusting the brightness based on the depths. The results of simulation show that the restored effect of this method is better for images which are degraded by weather under the environment of MATLAB.

To study the complex interactions between cloud processes and the atmosphere, several atmospheric models have been coupled with detailed spectral cloud microphysics schemes. These schemes are computationally expensive, which limits their practical application. Additionally, our performance analysis of the model system COSMO-SPECS (atmospheric model of the Consortium for Small-scale Modeling coupled with SPECtral bin cloud microphysicS) shows a significant load imbalance due to the cloud model. To overcome this issue and enable dynamic load balancing, we propose the separation of the cloud scheme from the static partitioning of the atmospheric model. Using the framework FD4 (Four-Dimensional Distributed Dynamic Data structures), we show that this approach successfully eliminates the load imbalance and improves the scalability of the model system. We present a scalability analysis of the dynamic load balancing and coupling for two different supercomputers. The observed overhead is 6% on 1600 cores of an SGI Altix 4700 and less than 7% on a BlueGene/P system at 64Ki cores.

The primitive variable formulation of the moist hydrostatic equations conserves mass and moist total energy due to the property that the divergence and gradient operators are adjoints. Any compatible numerical method, which has a discrete analog of this property will conserve a discrete mass and total energy. We demonstrate this using aqua-planet simulations performed with CAM-HOMME (NCAR’s Community Atmospheric Model with the High-Order Method Modeling Environment dynamical core). CAM-HOMME uses a compatible numerical method on arbitrary unstructured quadrilateral grid. The equations described here are the full set of dynamical equations used by CAM. Aqua-planet simulations use the full suite of physics parametrizations as well. The only simplification is the use of idealized surface conditions. We report on the magnitude of the total energy budget in the dynamical core including estimates for the non-adiabatic processes. The practice of fixing dry total energy as opposed to the conserved total moist energy is shown to generate a forcing of − 0. 56 W/m2.

This lecture describes the basics of hyperbolic systems as needed to solve the initial boundary value problem for hydrostatic atmospheric modeling. We examine the nature of waves in the hydrostatic primitive equations and how the modal decomposition can be used to effect a complete solution in the interior of an open domain. The relevance of the open boundary problem for the numerical problem of static and adaptive mesh refinement is discussed.

This chapter discusses the development of discontinuous Galerkin (DG) schemes for the hyperbolic conservation laws relevant to atmospheric modeling. Two variants of the DG spatial discretization, the modal and nodal form, are considered for the one- and two-dimensional cases. The time integration relies on a second- or third-order explicit strong stability-preserving Runge–Kutta method. Several computational examples are provided, including a solid-body rotation test, a deformational flow problem and solving the barotropic vorticity equation for an idealized cyclone. A detailed description of various limiters available for the DG method is given, and a new limiter with positivity-preservation as a constraint is proposed for two-dimensional transport. The DG method is extended to the cubed-sphere geometry and the transport and shallow water models are discussed.

Within the theoretical framework of some modern unification theories the constants of nature are functions of cosmological time. Since white dwarfs are long-lived, compact objects, they offer the possibility of testing a possible variation of the gravitational constant and, thus, to place constraints to these theories. We present full white dwarf evolutionary calculations in the case in which the gravitational constant G decreases with time. White dwarf evolution is computed in a self-consistent way, including the most up-to-date physical inputs. The evolutionary sequences also consider accurate outer boundary conditions provided by non-gray model atmospheres and a detailed core chemical composition that results from the calculation of the full evolution of progenitor stars. We find that the mechanical structure and the energy balance of the white dwarf are strongly modified by the presence of a varying G. In particular, for a rate of change of G larger than \(\dot{G}/G= - 1 \times 1{0}^{-12}\) yr − 1, the evolution of cool white dwarfs is markedly affected. The impact of a varying G is more notorious in the case of more massive white dwarfs.

This chapter aims to place the dynamical core of weather and climate models into the context of the model as a system of components. Building from basic definitions that describe models and their applications, the chapter details the component structure of a present-day atmospheric model. This facilitates the categorization of model components into types and the basic description of the dynamical core. An important point in this categorization is that the separation between ‘dynamics’ and ‘physics’ is not always clear; there is overlap. This overlap becomes more important as the spatial resolution of models increases, with resolved scales and parameterized processes becoming more conflated. From this categorization an oversimple, intuitive list of the parts of a dynamical core is made. Following this, the equations of motion are analyzed, and the design-based evolution of the dynamical core described in Lin (2004, Monthly Weather Review) is discussed. This leads to a more complete description of the dynamical core, which explicitly includes the specification of topography and grids on which the equations of motion are solved. Finally, a set of important problems for future consideration is provided. This set emphasizes the modeling system as a whole and the need to focus on physical consistency, on the scientific investigation of coupling, on the representation of physical and numerical dissipation (sub-scale mixing and filtering), and on the robust representation of divergent flows. This system-based approach of model building stands in contrast to a component-based approach and influences the details of component algorithms.

The dynamics of the global atmosphere is highly complex and multiscale. In this chapter a few aspects are discussed that are considered especially important for the design of numerical models of the atmosphere. Commonly used approximations to the governing equations are discussed. The dynamics of fast acoustic and inertio-gravity waves is briefly explained along with their role in maintaining the atmosphere close to hydrostatic and geostrophic balance. The balanced dynamics is exemplified through quasigeostrophic theory, which embodies the key ideas of advection and invertibility of potential vorticity. Finally, some important effects of nonlinearity are discussed, in particular the interaction between different scales and the transfer of energy and potential enstrophy across scales.

A wavelength band selection method for target detection is proposed in the paper, which is based on the fundamentals of radiative transfer in atmosphere. The method aims at improving target detection performance according to wavelength band selection in considering the target radiance, the background radiance, the atmospheric transmittance, and the response of the receiving system. The typical spectral data of the target-background contrast and the transmittance were computed by MODTRAN, with the midlatitude summer atmospheric model in the daytime, clouds free, urban aerosols models, spring-summer aerosol profiles and background stratospheric profiles extinction models. The analysis of the wavelength band was performed to the typical spectral data, thus the optimal detection wavelength band was selected.

This paper reports on the communications made at the 2009 ICOSAHOM meeting minisymposium on the challenges of high order methods in numerical weather prediction, with contributions from mathematicians as well as atmospheric and ocean modelers. Motivation for an investment in high order method development for numerical weather prediction is given in terms of the potential payoff in light of the current challenges in the field. Among other issues, the implementation of physical parameterizations with high order methods stands out as a yet-unexplored and potentially difficult challenge to resolve. Adaptivity is also expected by some to significantly advance the state-of-the-art but no consensus seems to be reached that it will be feasible. Among the recommendations expressed at the workshop are the need for demonstrated efficiency comparisons between high order and low order methods for a desired level of accuracy in resolving waves.

The chapters in Part I, Theory, describe in some detail the theory and methodology of data assimilation. This chapter will focus on the role of the predictive model in an assimilation system. There are numerous books on atmospheric modelling, their history, their construction, and their applications (e.g. Trenberth 1992 Randall 2000 Jacobson 2005). This chapter will focus on specific aspects of the model and modelling in data assimilation.

Regional atmospheric models are important tools for short-range weather predictions and future climate change assessment. The further enhancement of spatial resolution and development of physical parameterizations in these models need the effective implementation of the program code on multiprocessor systems. However, nowadays typical cluster systems tend to grow into very huge machines with over petaflop performance, while individual computing node design stays almost unchanged, and growth is achieved simply by using more and more nodes, rather than increasing individual node performance and keeping adequate power consuming. This leads to worse scalability of data-intensive applications due to increasing time consumption for data passing via clusters interconnect. Especially some of numerical algorithms (e.g. those solving the Poisson equation) satisfactorily scaling at previous generation cluster systems do not utilize the computational resources of clusters with thousands cores effectively. This prompts to study the performance of numerical schemes of regional atmospheric models on processor architectures significantly different from those used in conventional clusters. Our approach focuses on improving the performance of time explicit numerical schemes for Reynolds-averaged equations of atmospheric hydrodynamics and thermodynamics by parallelization on CellBE processors. The optimization of loops for numerical schemes with local data dependence pattern and with independent iterations is presented. Cell-specific workloading managers are built on top of existing numerical schemes implementations, conserving the original source code layout and bringing high speed-ups over serial version on QS22 blade server. Intercomparison between Cell and other multicore architectures is also provided. Targeting the next generation of MPI-CellBE hybrid cluster architectures, out method aims to provide additional scalability to MPI-based codes of atmospheric models and related applications.

An atmospheric model is demonstrated using the shafts of Garraf and its function as an example of the karstic dynamic in the vadose zone. The breakdown of the atmospheric composition in the Llamp shaft is shown and the hydroatmospherics relationship (CO2 – vadose water) is indicated.

The NASA mission MESSENGER fly-byed planet Venus on June 2007 on its route to Mercury. This chance was took to produce coordinated observations between Messenger and ESA Venus Express spacecrafts. This work shows spectra in the wavelength range between 320 and 1450nm retrieved with the instrument MASCS (Mercury Atmospheric and Surface Composition Spectrometer). Spectra are calibrated in absolute reflectivity (diffuse reflection by Venus clouds) and wavelength, and they are navigated in order to retrieve their position in the planet’s disk. Comparing synthetic spectra with these ones for each viewing geometry we will obtain information on the vertical distribution of cloud particulates between 60 and 75km height, approximately, as well as the SO2 abundance, among others. This will be combined with almost simultaneous data gathered by the visible and infrared spectrograph VIRTIS onboard Venus Express spacecraft. The results of the atmospheric modeling will be presented elsewhere.

The urban canopy (UC), the layer of the atmosphere between the ground and the top of the highest buildings, is the region where people live and human activities take place. Because of this importance (e.g., human health, preservation of buildings) significant efforts have been dedicated to its investigation. Such studies shed light on the high complexity of atmospheric circulations in the UC, primarily because of the presence of obstacles (buildings) large enough to strongly modify air flow and the thermal exchanges between these surfaces and the atmosphere. The high level of heterogeneity of the UC has been a challenge for atmospheric modeling in urban areas, even for mesoscale models with a typical resolution of the order of 1 km; the basic characteristics of the perturbations induced by the obstacles still remaining unresolved at this model resolution. Over the last decade, with the increase of computational processing power, several mesoscale modeling systems, each with different urban canopy parameterization (UCP) schemes, have been developed and applied with the primary aim of representing the subgrid effects of urban surfaces on their mean variables.

A framework for a fully implicit solution method is implemented into (1) the High Order Methods Modeling Environment (HOMME), which is a spectral element dynamical core option in the Community Atmosphere Model (CAM), and (2) the Parallel Ocean Program (POP) model of the global ocean. Both of these models are components of the Community Climate System Model (CCSM). HOMME is a development version of CAM and provides a scalable alternative when run with an explicit time integrator. However, it suffers the typical time step size limit to maintain stability. POP uses a time-split semi-implicit time integrator that allows larger time steps but less accuracy when used with scale interacting physics. A fully implicit solution framework allows larger time step sizes and additional climate analysis capability such as model steady state and spin-up efficiency gains without a loss in scalability. This framework is implemented into HOMME and POP using a new Fortran interface to the Trilinos solver library, ForTrilinos, which leverages several new capabilities in the current Fortran standard to maximize robustness and speed. The ForTrilinos solution template was also designed for interchangeability; other solution methods and capability improvements can be more easily implemented into the models as they are developed without severely interacting with the code structure. The utility of this approach is illustrated with a test case for each of the climate component models.