Search

To produce food for a growing world population, irrigated areas have increased from approximately 0.63 million km2 of land in 1900 to 3.1 million km2 of land in 2005. Despite this massive expansion, irrigation is still overlooked in most state-of-the-art Earth system models (ESMs) involved in the Coupled Model Intercomparison Project phase 6 (CMIP6). To our knowledge, only three CMIP6 models represent irrigation activities: CESM2, GISS-E2-1-G, and NorESM2-LM. Here, we investigate the role of irrigation on historical climate at global and regional scales by analyzing trends of key surface climate variables in CMIP6 simulations during 1900?2014. The three models including irrigation show distinct behavior from the 15 models without irrigation over intensively irrigated areas (i.e., >50% of grid cell area is equipped by irrigation): both annual (months that correspond to monthly air temperature higher than 274 K) mean latent heat flux (LHF) and soil moisture increase over time, in contrast to the modelswithout irrigation that show no trend or even a negative trend. The positive LHF trend over intensively irrigated areas in the irrigation-on models is consistent with three satellite-based LHF products. While annual (considering the warmest month in a year) warming trends are found in these regions for most of the no-irrigation models, the increase in LHF induces a cooling trend for the models with irrigation, which was not confirmed by observational air temperature data sets. These findings, supported by satellite data, indicate the importance of improved representation of land management in the next generation of ESM.

15 figures, 1 table., Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. The results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases., This work is part of the PGC2018-094341-B-I00 research project funded by the Ministry of Science and Innovation/FEDER. Additionally, Mario Morales-Hernández was partially supported by the U.S. Air Force Numerical Weather Modeling Program.

The paper details the method to couple a 1-D hydro-sedimentary model to a 2-D hydro-sedimentary model in order to represent the hydrodynamics and morphological processes during a flood event along a river. Tested on two field cases, the coupled model is stable even in the case of generalized overflow over the riverbanks or of levee breaching. For lateral coupling, the coupled model allows saving computational time compared to a full 2-D model and to provide valuable results concerning the flooding features as well as the evolution of the bed topography. However, despite a similar simplified representation of the sediment features in the 1-D and 2-D models, some discrepancies appear in the case of upstream/downstream coupling along a cross section perpendicular to the flow direction because the assumption of homogeneous velocity and concentration is not valid for estimating sediment transport. Further research is necessary to be able to define a suitable distribution of the sediments on the 1-D side of the boundary between the two models.

This paper presents a multi-layer railway ballast track and substructure model, where a coupled discrete and continuous method is used for macro-meso dynamic behaviour analysis under moving wheel loads. In this coupled model, the discrete element method (DEM) is utilised to build the superstructure of the ballast track (i.e. rail, fastener, sleeper and ballast layer), which considers the complex ballast shape and particle size distribution from mesoscopic level. The finite difference method (FDM) is used to simulate the substructure (i.e. subgrade and foundation) with a consideration of computing cost. And then, the coupled model is achieved by satisfying displacement, velocity and contact force compatibility between the FLAC and the PFC. Finally, the dynamic analysis is carried out by applying the wheel-rail forces obtained from a vehicle-track dynamics model into the coupled model. The DEM parameters of ballast particles are calibrated based on the results of the ballast direct shear tests, and the dynamic behaviour of railway ballast track and subgrade system is validated with the field measurement. Through the numerical analysis, it is confirmed that the coupled DEM/FDM model can reliably reflect macro-meso dynamic behaviour and accurately reveal the contact characteristics between the ballast layer and subgrade.

A control moment gyroscope (CMG) is a key actuator for spacecraft's attitude and stability control. But there exist micro-vibrations from high-speed flywheel, which will affect the performance of the spacecraft greatly. Due to the unbalanced mass and the supporting structure, the high-speed rotating flywheel could generate disturbance torque, which will be passed to the gimbal to deteriorate the gimbal servo system. At the same time, the rotation of the gimbal will increase the disturbance torque for gyroscopic effect. According · to the bearing theory, the stiffness of the bearing is affected by the load that applied on it, which results the influence on the flywheel vibration and the generated disturbance torque. This means that there is a coupling effect in the CMG. In this article, we focused on this coupling relationship between the flywheel vibration and the gimbal rotation in a single gimbal control moment gyroscope (SGCMG) system. Firstly, a vibration model of the flywheel with variable stiffness supporting is established. And the rotation model of the gimbal is also developed. The flywheel model and the gimbal model are coupled with each other through the variable stiffness supporting and gyroscope effect. Based on the numerical simulations the interactions among the bearing stiffness, the flywheel vibration and the gimbal rotation are analyzed. Finally, experiments are carried out on the prototype. The experimental results have verified the theoretical analysis and the simulations, and which would support the design of high-performance control system.

Reclaimed water is considered to be an important alternative to freshwater to solve the imbalance between the supply and demand of regional water resources; it is also recognized as an effective tool for alleviating ecological problems caused by insufficient water flow. Yiwu City is a typical area experiencing a water shortage in southeastern China because the regional water resources are limited. In this study, the multiple water resource allocations in Yiwu City are optimized, the complex coupling model of multiple water resource allocation is established, and both the economic and ecological effects of multiple water resource allocation in Yiwu City are simulated and analyzed. The simulation results of optimizing the multiple water resource allocations show an efficient way of reclaimed water utilization in this typical Chinese city. In order to ensure the future economic and social development of Yiwu City, it is necessary to introduce reclaimed water into different fields, such as residential water, industrial water, agricultural water, and environmental water. Reclaimed water has also proven to have a high capability for pollutant control and reduction, which is also important to the ecology and environmental protection.

In this paper, cross-dispersal is considered in a predator–prey model with a patchy environment. A new predator–prey model with cross-dispersal among patches is constructed. A new cross-dispersal matrix is established by the coupling relationship between vertices. First, an existence theorem of the positive equilibrium for the new model is obtained. Secondly, based on the idea of constructing Lyapunov functions and a graph-theoretical approach for coupled systems, sufficient conditions that the positive equilibrium of the new model is globally asymptotically stable in $R^{2n}_{+}$ R + 2 n are derived on a network with strongly connected graphs. Thirdly, based on the theory of asymptotically autonomous systems, Lyapunov functions method and graph theory, a stability theorem for the positive equilibrium of the new model is established on a complex network without strongly connected graphs. Finally, two examples are given to illustrate main results.

Mineral dust acts both as a tracer and a forcing agent of climate change. Past dust variability, imprinted in paleodust records from natural archives, offers the unique opportunity to reconstruct the global dust cycle within a range of possibilities that plausibly encompass future variations in response to climate change and land-cover and land-use changes. Dust itself has direct and indirect feedbacks on the climate system, through impacts on the atmosphere radiative budget and the carbon cycle. Starting from well-constrained reconstructions of the present and past dust cycle, we focus on quantifying dust direct impacts on the atmospheric radiation. We discuss the intrinsic effects of dust onto climate, and how changes in the global dust budget and surface conditions modulate the effective impacts on surface temperatures and precipitation. Most notably, the presence of dust tends to enhance the West African monsoon and warm the Arctic. We also highlight how different choices in terms of dust optical properties and size distributions may yield opposite results, and what are the observational constraints we can use to make an informed choice of model parameters. Finally, we discuss how dust variability might have influenced ongoing climate transitions in the past. In particular we found that a reduction in dust load, along with a reduced cryosphere cover, acted to offset Arctic warming during the deglaciation, potentially playing a role in shaping the Northern Hemisphere deglacial dynamics.

The September 2018, Mw 7.5 Sulawesi earthquake occurring on the Palu-Koro strike-slip fault system was followed by an unexpected localized tsunami. We show that direct earthquake-induced uplift and subsidence could have sourced the observed tsunami within Palu Bay. To this end, we use a physics-based, coupled earthquake–tsunami modeling framework tightly constrained by observations. The model combines rupture dynamics, seismic wave propagation, tsunami propagation and inundation. The earthquake scenario, featuring sustained supershear rupture propagation, matches key observed earthquake characteristics, including the moment magnitude, rupture duration, fault plane solution, teleseismic waveforms and inferred horizontal ground displacements. The remote stress regime reflecting regional transtension applied in the model produces a combination of up to 6 m left-lateral slip and up to 2 m normal slip on the straight fault segment dipping 65∘ East beneath Palu Bay. The time-dependent, 3D seafloor displacements are translated into bathymetry perturbations with a mean vertical offset of 1.5 m across the submarine fault segment. This sources a tsunami with wave amplitudes and periods that match those measured at the Pantoloan wave gauge and inundation that reproduces observations from field surveys. We conclude that a source related to earthquake displacements is probable and that landsliding may not have been the primary source of the tsunami. These results have important implications for submarine strike-slip fault systems worldwide. Physics-based modeling offers rapid response specifically in tectonic settings that are currently underrepresented in operational tsunami hazard assessment. ISSN:0033-4553 ISSN:1420-9136 ISSN:1557-7368

Strongly coupled data assimilation (SCDA) views the Earth as one unified system. This allows observations to have an instantaneous impact across boundaries such as the air‐sea interface when estimating the state of each individual component. Operational prediction centers are moving toward Earth system modeling for all forecast timescales, ranging from days to months. However, there have been few studies that examine fundamental aspects of SCDA and the transition from traditional approaches that apply data assimilation only to a single component, whether forecasts were derived from a coupled model or an uncoupled forced model. The SCDA approach is examined here in detail using numerical experiments with a simple coupled atmosphere‐ocean quasi‐geostrophic model. The impact of coupling is explored with respect to its impact on the Lyapunov spectrum and on data assimilation system stability. Different data assimilation methods are compared within the context of SCDA, including the 3‐D and 4‐D Variational methods, the ensemble Kalman filter, and the hybrid gain method. The impact of observing system coverage is also investigated. We find that SCDA is generally superior to weakly coupled or uncoupled approaches. Dynamically defined background error covariance estimates are essential for SCDA to achieve an accurate coupled state estimate as the observing system becomes sparser. As a clarification of seemingly contradictory findings from previous studies, it is shown that ocean observations can adequately constrain atmospheric state estimates provided that the analysis‐observing frequency is sufficiently high and the ensemble size determining the background error covariance is sufficiently large.

With the motivation to improve the simulation of the East Asian summer monsoon (EASM) in coupled climate models, oceanic data assimilation (DA) was used in CAS-ESM-C (Chinese Academy of Sciences–Earth System Model–Climate Component) in this study. Observed sea surface temperature was assimilated into CAS-ESM-C. The climatology and interannual variability of the EASM simulated in CAS-ESM-C with DA were compared with a traditional AMIP-type run. Results showed that the climatological spatial pattern and annual cycle of precipitation in the western North Pacific, and the ENSO-related and EASM-related EASM circulation and precipitation, were largely improved. As shown in this study, air–sea coupling is important for EASM simulation. In addition, oceanic DA synchronizes the coupled model with the real world without breaking the air–sea coupling process. These two successful factors make the assimilation experiment a more reasonable experimental design than traditional AMIP-type simulations.

Detecting motor bearing faults by stator currents is of great importance as it improves the adaptability of measurement means to different environments and reduces the number of sensors. Therefore, many studies have been conducted to investigate bearing faults by constructing motor models, most of which have used signal models to simulate the dynamics of the bearings. However, the signal model may be exposed to the issue that the nonlinearities in the bearing operation are neglected, thus oversimplifying the coupling effects between the electromagnetic and dynamics models. Hence, a coupled electromagnetic–dynamic modeling method for induction motors based on multiple coupled circuit theory and the rotor-bearing dynamics model is proposed in this study to implement the coupled simulation of electromagnetic and dynamic models. The air gap length and rotor velocity are used as coupled parameters for the calculation of stator–rotor mutual inductance and ball contact deformation, respectively. The simulation results show that the proposed model can effectively implement the electromagnetic–dynamic coupled and reflect the bearing fault characteristics in the current signal. Experiments were conducted on induction motors with typical winding configurations under laboratory conditions. The comparison results verify the effectiveness of the proposed modeling method.

Surface waves modify upper ocean dynamics through Stokes drift related processes. Stokes drift estimated from a discrete wave spectrum is compared to Stokes drift approximations as a monochromatic profile based on bulk surface wave parameters, and to two additional superexponential functional forms. The impact of these different methods on ocean processes is examined in two test‐bed cases of a wave‐current coupled system: (1) a wind‐free shallow water inlet test case and (2) an idealized deep water hurricane case with high varying winds. In case (1), tidal currents and bathymetry can modify the waves and significantly affect Stokes drift computed from the wave spectrum. In case (2), rapid variation in atmospheric stress at high wind speed generates large departures from fully developed equilibrium seas. In both cases, large deviations in ocean current response are produced when the Stokes drift is approximated monochromatically from bulk wave parameters, rather than from integration over the wave spectra. Deep water simulations using the two superexponential approximations are in better agreement with those estimated from wave spectra than are those using the monochromatic, exponential profile based on bulk wave parameters. In order to represent the impact of Stokes drift at resolved scales, we recommend that for studies of nearshore processes and deep water events, like wave‐current interactions under storms, the Stokes drift should be calculated from full wave spectra. For long simulations of open ocean dynamics, methods using superexponential profiles to represent equilibrium wind seas might be sufficient, but appear to be marginally more computationally efficient.

Aerial manipulation is an emerging field of research, and important applications can be envisaged, such as inspection and maintenance, search and rescue, structure assembly, and logistics. The manipulator transfers forces and torques to the UAV, which affect the UAV position and attitude. This may cause failure or loss of precision in pick and place and assembly operations. In this paper, first, the effect of simple impulsive force and torque disturbances on UAV dynamics is studied. Then, a coupled dynamic model of the UAV and a 1-DOF (Degree of Freedom) manipulator is developed and compared to a simplified decoupled model. Finally, a decoupled dynamic model is proposed for a 3-DOFs manipulator, and the simulation results for a real pick and place operation are presented and discussed. It is evidenced that, in all of the considered scenarios, a lateral displacement of the system is generated during the manipulation in hovering flight, which could jeopardize the manipulator precision.

Jack-up offshore platform is a type of important marine structure, which is mainly used for satellite launch, oil exploitation, and other engineering tasks in the offshore area. The offshore platform is bound to be subjected to wave loading in the course of use. Whether it can withstand the wave impact is an important engineering problem. To solve this engineering problem, the self-developed fluid–structure–foundation interaction coupling model OlaFlow-ABAQUS is used to explore the dynamic response characteristics of a jack-up offshore platform and its seabed foundation under three conventional wave conditions (wave height is 3, 5, and 7 m, respectively) in a coupled way. The numerical results show that only a small amplitude of periodic sloshing occurs for the jack-up offshore platform under the three conventional wave conditions. The maximum sloshing amplitude is up to 8 cm, and there is no visible residual displacement. It is indicated that there is no plastic deformation zone in the seabed foundation near the pile legs of the jack-up platform. It can thus be concluded that the jack-up platform has excellent stability under conventional wave conditions. Under conventional wave loading, momentary liquefaction occurs in the seabed foundation around the pile legs of the platform, and the maximum liquefaction depth is about 1 m. This study indicates that the coupling model OlaFlow-ABAQUS for the fluid–structure–foundation interaction is feasible, and has some advantages to study the dynamic response and to evaluate the stability of large-scale marine structures and their seabed foundations under ocean waves.

Climate models contain atmospheric and oceanic components that are coupled together to simulate the thermodynamic and dynamic processes during air‐sea interactions. Community Earth System Model (CESM version 1.2.1) is a state‐of‐the‐art coupled model that is widely used and participates in Coupled Model Intercomparison Projects. Community Atmospheric Model (CAM), the atmospheric component of CESM, is based on the finite‐volume dynamic core, which utilizes staggered Arakawa‐D grids. However, the dynamics‐physics (D‐P) coupling in CAM causes the prognostic winds of the dynamic core be interpolated onto non‐staggered locations, which affects the wind structure for computing the air‐sea interaction and dynamical coupling. In this study we propose a new scheme that eliminates the extra interpolation during D‐P coupling for the atmosphere‐ocean interaction. We show that it improves the simulated climatology in key regions including eastern boundary upwelling regions and Southern Oceans. Compared with the default scheme, the new approach simulates strong surface wind near coast in eastern boundary upwelling regions. As a result, existing problems of the model, such as warm SST biases in these regions, are reduced. Meanwhile, for Southern Ocean, the prevailing westerlies are enhanced in new scheme, resulting in meridional sea ice transport. As a result, the overestimation of sea ice extent and negative bias in SST is reduced. This new scheme is generally applicable to coupled models with staggered dynamics‐physics, such as spectral‐element method based CAM.

The shape and extent of the Greenland Ice Sheet (GIS) during the Last Interglacial (LIG) is a matter of controversy, with different studies proposing a wide range of reconstructions. Here, for the first time, we combine stable water isotopic information from ice cores with isotope-enabled climate model outputs to investigate the problem. Exploring the space of possible ice sheet geometries by simulation is prohibitively expensive. We address this problem by using a Gaussian process emulator as a statistical surrogate of the full climate model. The emulator is calibrated using the results of a small number of carefully chosen simulations and then permits fast, probabilistic predictions of the simulator outputs at untried inputs. The inputs are GIS morphologies, parameterized through a dimension-reduction technique adapted to the spherical geometry of the setting. Based on the emulator predictions, the characteristics of morphologies compatible with the available ice core measurements are explored, leading to a reduction in uncertainty on the LIG GIS morphology. Moreover, a scenario-based approach allows to assess the gains in uncertainty reduction which would result from the availability of better dated LIG measurements in Greenland ice cores.

For the first time, a comprehensive study of downward flame spread over glass-fiber-reinforced epoxy resin (GFRER) slabs in oxidizer flow has been carried out experimentally and numerically. Microthermocouples were used to measure the temperature profiles on the solid fuel’s surface and in the flame, and a video camera was used to measure the rate of flame spread (ROS). The ROS was found to be linearly dependent on the oxygen concentration, to be inversely proportional to the slab thickness and not to depend on the direction of the flame spread over the slab. The absence of the influence of the forced oxidizing flow velocity and the weak influence of the GFRER pyrolysis kinetics on the ROS were observed. For the first time, a numerical model of flame spread over reinforced material with thermal conductivity anisotropy was developed on the basis of a coupled ‘gas–solid’ heat and mass transfer model, using modifications of the OpenFOAM open-source code. The sensitivity analysis of the model showed that the thermal conductivity in the normal direction to the GFRER surface had a much greater effect on the ROS than the thermal conductivity along the direction of flame propagation. The numerical results show good agreement with the experimental data on the dependences of the ROS on oxygen concentration, slab thickness and the N2/O2 mixture flow velocity, as well as temperature distributions on the fuel surface, the maximum flame temperatures and the flame zone length.

All the weather and climate models participating in the Clouds Above the United States and Errors at the Surface project show a summertime surface air temperature (T2m) warm bias in the region of the central United States. To understand the warm bias in long-term climate simulations, we assess the Atmospheric Model Intercomparison Project simulations from the Coupled Model Intercomparison Project Phase 5, with long-term observations mainly from the Atmospheric Radiation Measurement program Southern Great Plains site. Quantities related to the surface energy and water budget, and large-scale circulation are analyzed to identify possible factors and plausible links involved in the warm bias. The systematic warm season bias is characterized by an overestimation of T2m and underestimation of surface humidity, precipitation, and precipitable water. Accompanying the warm bias is an overestimation of absorbed solar radiation at the surface, which is due to a combination of insufficient cloud reflection and clear-sky shortwave absorption by water vapor and an underestimation in surface albedo. The bias in cloud is shown to contribute most to the radiation bias. The surface layer soil moisture impacts T2m through its control on evaporative fraction. The error in evaporative fraction is another important contributor to T2m. Similar sources of error are found in hindcast from other Clouds Above the United States and Errors at the Surface studies. In Atmospheric Model Intercomparison Project simulations, biases in meridional wind velocity associated with the low-level jet and the 500hPa vertical velocity may also relate to T2m bias through their control on the surface energy and water budget.

The Coupled Model Intercomparison Project (CMIP) is now moving into its sixth phase and aims at a more routine evaluation of the models as soon as the model output is published to the Earth System Grid Federation (ESGF). To meet this goal the Earth System Model Evaluation Tool (ESMValTool), a community diagnostics and performance metrics tool for the systematic evaluation of Earth system models (ESMs) in CMIP, has been developed and a first version (1.0) released as open source software in 2015. Here, an enhanced version of the ESMValTool is presented that exploits a subset of Essential Climate Variables (ECVs) from the European Space Agency's Climate Change Initiative (ESA CCI) Phase 2 and this version is used to demonstrate the value of the data for model evaluation. This subset includes consistent, long-term time series of ECVs obtained from harmonized, reprocessed products from different satellite instruments for sea surface temperature, sea ice, cloud, soil moisture, land cover, aerosol, ozone, and greenhouse gases. The ESA CCI data allow 'extending the calculation of performance metrics as summary statistics for some variables and add an important alternative data set in other cases where observations are already available. The provision of uncertainty estimates on a per grid basis for the ESA CCI data sets is used in a new extended version of the Taylor diagram and provides important additional information for a more objective evaluation of the models. In our analysis we place a specific focus on the comparability of model and satellite data both in time and space. The ESA CCI data are well suited for an evaluation of results from global climate models across ESM compartments as well as an analysis of long-term trends, variability and change in the context of a changing climate. The enhanced version of the ESMValTool is released as open source software and ready to support routine model evaluation in CMIP6 and at individual modeling centers. (C) 2017 Elsevier Inc. All rights reserved.

Data assimilation has been widely applied in atmospheric and oceanic forecasting systems and particle filters (PFs) have unique advantages in dealing with nonlinear data assimilation. They have been applied to many scientific fields, but their application in geoscientific systems is limited because of their inefficiency in standard settings systems. To address these issues, this paper further refines the statistical observation and localization scheme which used in the classic localized equivalent-weights particle filter with statistical observation (LEWPF-Sobs). The improved method retains the advantages of equivalent-weights particle filter (EWPF) and the localized particle filter (LPF), while further refinements incorporate the effect of time series on the reanalyzed data into the statistical observation calculations, in addition to incorporating the statistical observation proposal density into the localization scheme to further improve the assimilation accuracy under sparse observation conditions. In order to better simulate the geoscientific system, we choose an intermediate atmosphere-ocean-land coupled model (COAL-IC) as the experimental model and divide the experiment into two parts: standard observation and sparse observation, which are analyzed by the spatial distribution results and root mean square error (RMSE) histogram. In order to better analyze the characteristics of the improved method, this method was chosen to be analyzed in comparison with the localized weighted ensemble Kalman filter (LWEnKF), the LPF and classical LEWPF-Sobs. From the experimental results, it can be seen that the improved method is better than the LWEnKF and LPF methods for various observation conditions. The improved method reduces the RMSE by about 7% under standard observation conditions compared to the traditional method, while the advantage of the improved method is even more obvious under sparse observation conditions, where the RMSE is reduced by about 85% compared to the traditional method. In particular, this improved filter not only combine the advantage of the two algorithms, but also overcome the computing resources.

Due to the model and sampling errors of the finite ensemble, the background ensemble spread becomes small and the error covariance is underestimated during filtering for data assimilation. Because of the constraint of computational resources, it is difficult to use a large ensemble size to reduce sampling errors in high-dimensional real atmospheric and ocean models. Here, based on Bayesian theory, we explore a new spatially and temporally varying adaptive covariance inflation algorithm. To increase the statistical presentation of a finite background ensemble, the prior probability of inflation obeys the inverse chi-square distribution, and the likelihood function obeys the t distribution, which are used to obtain prior or posterior covariance inflation schemes. Different ensemble sizes are used to compare the assimilation quality with other inflation schemes within both the perfect and biased model frameworks. With two simple coupled models, we examined the performance of the new scheme. The results show that the new inflation scheme performed better than existing schemes in some cases, with more stability and fewer assimilation errors, especially when a small ensemble size was used in the biased model. Due to better computing performance and relaxed demand for computational resources, the new scheme has more potential applications in more comprehensive models for prediction initialization and reanalysis. In a word, the new inflation scheme performs well for a small ensemble size, and it may be more suitable for large-scale models.

This study aimed to explore the diversity of open-innovation practices that are adopted in Portuguese SMEs considering the outside-in, inside-out, and coupled paradigms. A quantitative study was carried out considering a sample of 187 Portuguese SMEs. The findings revealed that these organizations favored the adoption of the outside-in paradigm. The inside-out model was the least relevant, especially for smaller companies (i.e., small and micro-companies). The most adopted outside-in practices were the integration of external knowledge from suppliers and clients, in the inside-out model, licensing processes were more important, while in the coupled model, joint ventures and network consortiums stood out. The increase in the innovation capacity of these organizations was highlighted as the most relevant benefit, while the lack of resources and difficulties in integrating knowledge emerged as challenges. This study is especially relevant for the establishment of public-support policies that promote the involvement of Portuguese SMEs in open-innovation processes.

International audience; The greenhouse design as well as the cover material properties in particular may strongly impact the greenhouse energy. To study the effect of these parameters, three typical unheated greenhouses equipped with rows of canopy were considered. Experiments were launched to establish the boundary conditions and validate the model. Two parametric studies were carried out: for the nocturnal period when the energy performance of each type of greenhouse was investigated, and for the diurnal period, when the sun path was simulated taking into account the type of the cover, its spectral optical and thermal properties. Results indicate that for the nocturnal period, the ambient air temperature in the tunnel and vertical wall greenhouse was relatively homogenous and warmer compared with the temperature distribution in the Venlo greenhouse. The plastic greenhouse, especially the tunnel one had better performances concerning the homogenization of the climate and the thermal energy storage. Concerning the diurnal period, and for both plastic greenhouses equipped with fully opened side vents, the air located between the rows of canopy and ground surfaces remained very slow, not exceeding 0.2 ms-1; for the Venlo glasshouse, the recirculation loop situated above the crop improved the air mixing and induced a good homogenization. Results indicate that the cover material with highest absorptivity, deteriorated the natural ventilation, increasing the air temperature by convection, and reduced the available Photosynthetically Active Radiation.

International audience; Greenhouse design and cover material properties may strongly impact greenhouse energy. To study the effect of these parameters, three typical unheated agricultural buildings equipped with rows of canopy were considered, and two-dimensional simulations were conducted using the discrete ordinate model for simulating radiative transfers. Experiments were conducted to establish the boundary conditions and to validate the model. Two parametric studies were carried out: one for the nocturnal period when the energy performance of each type of greenhouse was investigated, and one for the diurnal period, when the sun path was simulated taking into account the type of the cover, its spectral optical and thermal properties. Results indicate that for the diurnal period, and for both plastic greenhouses equipped with fully opened side vents, the air located between the rows of canopy and ground surfaces remained very slow, not exceeding 0.2 m/s; for the Venlo glasshouse, the recirculation loop situated above the crop improved the air mixing and induced a good homogenization. Results also indicate that the cover material with the highest absorptivity, deteriorated the natural ventilation, increasing the air temperature by convection, enhancing local air temperature favoring the development of a secondary recirculation, and reduced the available photosynthetically active radiation. Concerning the nocturnal period, the ambient air temperature in the tunnel and in the vertical wall of the greenhouse was relatively homogenous and warmer than the temperature in the Venlo greenhouse. During the nocturnal period, the plastic greenhouse (in particular the one with the tunnel) performed better in regard to the homogenization of the climate and thermal energy storage.

Through tropical cyclone (TC) activity the ocean and the atmosphere exchange a large amount of energy. In this work possible improvements introduced by a higher coupling frequency are tested between the two components of a climate model in the representation of TC intensity and TC–ocean feedbacks. The analysis is based on the new Centro Euro-Mediterraneo per I Cambiamenti Climatici Climate Model (CMCC-CM2-VHR), capable of representing realistic TCs up to category-5 storms. A significant role of the negative sea surface temperature (SST) feedback, leading to a weakening of the cyclone intensity, is made apparent by the improved representation of high-frequency coupled processes. The first part of this study demonstrates that a more realistic representation of strong TC count is obtained by coupling atmosphere and ocean components at hourly instead of daily frequency. Coherently, the positive bias of the annually averaged power dissipation index associated with TCs is reduced by one order of magnitude when coupling at the hourly frequency, compared to both forced mode and daily coupling frequency results. The second part of this work shows a case study (a modeled category-5 typhoon) analysis to verify the impact of a more realistic representation of the high-frequency coupling in representing the TC effect on the ocean; the theoretical subsurface warming induced by TCs is well represented when coupling the two components at the higher frequency. This work demonstrates that an increased horizontal resolution of model components is not sufficient to ensure a realistic representation of intense and fast-moving systems, such as tropical and extratropical cyclones, but a concurrent increase in coupling frequency is required.

The SINTEX‐F1 Coupled General Circulation Model (CGCM) was developed within the EU‐Japan collaborative framework to study global climate variability and its predictability by use of the Earth Simulator. The seasonal prediction system based on the SINTEX‐F1 has demonstrated its outstanding performance of predicting El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole since 2005. However, there is much room for improvement in predicting extratropical climate variations. To deal with this, a revised CGCM called SINTEX‐F2 has been developed; the new system is a high‐resolution version with a dynamical sea‐ice model. For the tropical climate variations in the Pacific and the Indian Ocean, the SINTEX‐F2 preserves the high‐prediction skill, and sometimes even shows higher skill especially for strong events, as compared to the SINTEX‐F1. In addition, it has turned out that the new system is more skillful in predicting the subtropics, particularly, the Indian Ocean Subtropical Dipole and the Ningaloo Niño. The improvement may contribute to enhancing prediction skills of the regional rainfall distributions and encourage us to develop an early warning system which may be applied for societal and industrial activities.

In general, modeling of photovoltaic-thermoelectric (PV/TEG) hybrid panels have been mostly simplified and disconnected from the actual ambient conditions and thermal losses from the panel. In this study, a thermally coupled model of PV/TEG panel is established to precisely predict performance of the hybrid system under different weather conditions. The model takes into account solar irradiation, wind speed and ambient temperature as well as convective and radiated heat losses from the front and rear surfaces of the panel. The model is developed for three sample cities in Europe with different weather conditions. The results show that radiated heat loss from the front surface and the convective heat loss due to the wind speed are the most critical parameters on performance of the hybrid panel performance. The results also indicate that, with existing thermoelectric materials, the power generation by the TEG is insignificant compared to electrical output by the PV panel, and the TEG plays only a small role on power generation in the hybrid PV/TEG panel. However, contribution of the TEG in the power generation can be improved via higher ZT thermoelectric materials and geometry optimization of the TEG.

The suitable groundwater exploitation scheme in freezing-thawing agricultural areas under the well-canal conjunctive irrigation conditions is confronted with two major challenges, which are computationally expensive local grid refinements along wells, and the model suitability problem in the freezing-thawing period. In this study, an empirical method for groundwater level prediction in the freezing-thawing period was developed and integrated with the local grid refinement groundwater model MODFLOW-LGR for the groundwater process prediction. The model was then applied to estimate the suitable groundwater exploitation scheme, including the size of well-irrigated area and the irrigation area of single well. The results showed that suitable size of well-irrigated area should be smaller than 15 × 106 m2, and the recommended irrigation area of single well as 15 × 104 m2 to 19 × 104 m2. The recommended layout parameters of groundwater exploitation were further used to plan the well-canal conjunctive irrigation scheme in Yongji irrigation district located in northern China. This study provides an important pilot example of the conjunctive use of groundwater and surface water in arid irrigation areas with a seasonal freezing-thawing period.

Improving the understanding of the stabilization process is of great significance to guide the sustainable development of municipal solid waste (MSW) landfills. An evaluation system of the stabilization process of MSW landfills has been established. The indices of the evaluation system involve the degradation degree of MSW, the release of landfill gas production potential, and the settlement of landfills. Based on the biochemical-consolidation-solute migration coupled model, an evaluation method of the MSW landfill stabilization process is proposed by combining field tests with numerical simulation. The stabilization process of the Jiangcungou landfill in China is investigated by using the proposed method. The analyzed results show that the stabilization process of high kitchen waste content landfills can be divided into three stages, which is different from the stabilization process of landfills in developed countries. For the Jiangcungou landfill, the ratio of cellulose to lignin in MSW decreases rapidly during the fast degradation stage when obvious settlement occurs. During the slow degradation stage, the hydrolysis rate is slow and settlement develops slowly. When the landfill reaches the stabilization stage, the ratio of cellulose to lignin of MSW changes very slowly, most of the landfill gas potential has been released, the settlement stabilization is completed basically. The change processes of the three evaluation indices are different, of which the degradation stabilization index is the main one. According to the findings above, leachate recirculation is recommended to adjust the degradation environment in the landfill, which can be helpful to avoid acidification at the fast degradation stage. Temporary cover is suggested to improve landfill gas collection efficiency at the beginning of the stable methanogenic stage. The landfill site closure should be operated when the settlement rate is low.

There is a significant interaction between wind and earthquakes for large-scaled wind turbines due to an aeroelastic effect. This study evaluates the accuracy of an uncoupled method extensively utilized to analyze the seismic response of wind turbines at the operational state. Initially, the oscillation of the blade for the National Renewable Energy Laboratory (NREL) 5 MW wind turbine excited by wind and wind-earthquake combination, respectively, is compared using the fully coupled method to verify the assumption in this uncoupled method. Subsequently, the influence of ground motions on the aerodynamic loadings of the rotor is discussed to evaluate the interaction between wind and earthquake loads. In addition, the accuracy of the uncoupled method is assessed by comparing the analysis results of the coupled and uncoupled methods, where different mean wind speed and equivalent aerodynamic damping ratio are considered. The results indicate that the oscillation velocity of blades and thrust on the rotor are significantly influenced by ground motions. Moreover, the amplitude of thrust variations caused by earthquakes increases monotonously with the oscillation velocity amplitude of blade-root. The errors between the two models are beyond the engineering margins for some earthquakes, such that it is difficult to optimize a consistent aerodynamic damping in the uncoupled model to accurately predict the seismic response of wind turbines.

A coupled floating body-mooring line model is developed by combining a boundary element model for a two-dimensional floating body and a catenary mooring line model. The boundary element model is formulated in the time domain by a continuous Rankine source, and a reflection potential is introduced to account for the wave reflection due to sloping seabed. This newly developed model is validated by comparisons against available data. Then, dynamic response analyses are performed for the moored body in various seabed conditions. Compared with a flat seabed, a sloping seabed causes unsymmetrical mooring line configuration and generates noticeable effects in the motion responses of the floating body.

In this paper, the stability problem of a new coupled model constructed by two fractional-order differential equations for every vertex is studied. The coupled relationship is hybrid. By using the method of constructing Lyapunov functions based on graph-theoretical approach for coupled systems, sufficient conditions that the coexistence equilibrium of the coupling model is globally Mittag–Leffler stable in $R^{2n}$ are derived. An example is given to illustrate the main results.

Ensembles of retrospective 2-month dynamical forecasts initiated on 1 May are used to predict the onset of the Indian summer monsoon (ISM) for the period 1989–2005. The subseasonal predictions (SSPs) are based on a coupled general circulation model and recently they have been upgraded by the realistic initialization of the atmosphere with initial conditions taken from reanalysis. Two objective large-scale methods based on dynamical-circulation and hydrological indices are applied to detect the ISM onset. The SSPs show some skill in forecasting earlier-than-normal ISM onsets, while they have difficulty in predicting late onsets. It is shown that significant contribution to the skill in forecasting early ISM onsets comes from the newly developed initialization of the atmosphere from reanalysis. On one hand, atmospheric initialization produces a better representation of the atmospheric mean state in the initial conditions, leading to a systematically improved monsoon onset sequence. On the other hand, the initialization of the atmosphere allows some skill in forecasting the northward-propagating intraseasonal wind and precipitation anomalies over the tropical Indian Ocean. The northward-propagating intraseasonal modes trigger the monsoon in some early-onset years. The realistic phase initialization of these modes improves the forecasts of the associated earlier-than-normal monsoon onsets. The prediction of late onsets is not noticeably improved by the initialization of the atmosphere. It is suggested that late onsets of the monsoon are too far away from the start date of the forecasts to conserve enough memory of the intraseasonal oscillation (ISO) anomalies and of the improved representation of the mean state in the initial conditions.

The offline linearized ocean–atmosphere model (LOAM), which was developed to quantify the impact of the climatological mean state on the variability of the El Niño–Southern Oscillation (ENSO), is used to illuminate why ENSO changed between the modern-day and early/mid-Holocene simulations in two climate modeling studies using the NCAR Climate System Model (CSM) and the Hadley Centre Coupled Model, version 3 (HadCM3). LOAM reproduces the spatiotemporal variability simulated by the climate models and shows both the reduction in the variance of ENSO and the changes in the spatial structure of the variance during the early/mid-Holocene. The mean state changes that are important in each model are different and, in both cases, are also different from those hypothesized to be important in the original papers describing these simulations. In the CSM simulations, the ENSO mode is stabilized by the mean cooling of the SST. This reduces atmospheric heating anomalies that in turn give smaller wind stress anomalies, thus weakening the Bjerknes feedback. Within the ocean, a change in the thermocline structure alters the spatial pattern of the variance, shifting the peak variance farther east, but does not reduce the overall amount of ENSO variance. In HadCM3, the ENSO mode is stabilized by a combination of a weaker thermocline and weakened horizontal surface currents. Both of these reduce the Bjerknes feedback by reducing the ocean’s SST response to wind stress forcing. This study demonstrates the importance of considering the combined effect of a mean state change on the coupled ocean–atmosphere system: conflicting and erroneous results are obtained for both models if only one model component is considered in isolation.

This paper introduces a newly established coupled atmosphere-ocean-ice system with the regional climate model COSMO-CLM and the ocean-sea-ice model NEMO for the North and Baltic Seas. These two models are linked via the OASIS3 coupler. Experiments with the new coupled system and with the stand-alone COSMO-CLM model forced by ERA-Interim re-analysis data over the period from 1985 to 1994 for the CORDEX Europe domain are carried out. The evaluation results of the coupled system show 2-m temperature biases in the range from − 2.5 to 3 K. Simulated 2-m temperatures are generally colder in the coupled than in the uncoupled system, and temperature differences vary by season and space. The coupled model shows an improvement compared with the stand-alone COSMO-CLM in terms of simulating 2-m temperature. The difference in 2-m temperature between the two experiments are explained as downwind cooling by the colder North and Baltic Seas in the coupled system.

Outputs from coupled general circulation models (CGCMs) are used in examining tropical Pacific decadal variability (TPDV) and their relationships with El Niño–Southern Oscillation (ENSO). Herein TPDV is classified as either ENSO-induced TPDV (EIT) or ENSO-like TPDV (ELT), based on their correlations with a decadal modulation index of ENSO amplitude and spatial pattern. EIT is identified by the leading EOF mode of the low-pass filtered equatorial subsurface temperature anomalies and is highly correlated with the decadal ENSO modulation index. This mode is characterized by an east–west dipole structure along the equator. ELT is usually defined by the first EOF mode of subsurface temperature, of which the spatial structure is similar to ENSO. Generally, this mode is insignificantly correlated with the decadal modulation of ENSO. EIT closely interacts with the residuals induced by ENSO asymmetries, both of which show similar spatial structures. On the other hand, ELT is controlled by slowly varying ocean adjustments analogous to a recharge oscillator of ENSO. Both types of TPDV have similar spectral peaks on a decadal-to-interdecadal time scale. Interestingly, the variances of both types of TPDV depend on the strength of connection between El Niño–La Niña residuals and EIT, such that the strong two-way feedback between them enhances EIT and reduces ELT. The strength of the two-way feedback is also related to ENSO variability. The flavors of El Niño–La Niña with respect to changes in the tropical Pacific mean state tend to be well simulated when ENSO variability is larger in CGCMs. As a result, stronger ENSO variability leads to intensified interactive feedback between ENSO residuals and enhanced EIT in CGCMs.

Satellites and several specially equipped scientific aircraft provide basin-wide altimetric measurements of sea ice freeboard, from which sea ice thickness can be estimated. Up to now, few methods have been developed to use these measurements to quantitatively assess the skill of predictive models of sea ice for the Arctic. This thesis addresses this problem, using measured freeboard from ICESat and Operation IceBridge (OIB). Output from the Regional Arctic System Model (RASM) is used to demonstrate applicability of both variance- and correlation-weighted skill scores of freeboard that quantify model skill and take measurement error into account. The techniques are demonstrated using two different RASM configurations, one using Elastic-Viscous-Plastic (EVP) ice mechanics, the other using the Elastic- Anisotropic-Plastic (EAP) rheology, both simulated for 2004 and 2007, during which ICESat was in operation. RASM variance skill scores ranged from 0.712 to 0.824 and correlation skill scores were between 0.319 and 0.511. The skill scores were calculated for monthly periods and require little adaption to be applicable for monthly to decadal Navy forecasts of the Arctic. This will help improve sea ice prediction by quantifying model limitations and thus maximize the usefulness of ICESat-2 freeboard measurements after that satellite is launched next year. http://archive.org/details/quantifyingseaso1094549374 Lieutenant, United States Navy Approved for public release; distribution is unlimited.

International audience; Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO 2 levels. On the one hand, elevated CO 2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Boli-vian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3 • C by 2100 which drives up the evaporative demand, whereby Published by Copernicus Publications on behalf of the European Geosciences Union. 1456 M. Guimberteau et al.: Impacts of future deforestation and climate change on the Amazon hydrology precipitation increases by 8.5%, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14 %, respectively. However, in southeast Amazonia, precipitation decreases by 10 % at the end of the dry season and the three LSMs produce a 6 % decrease of ET, which is less than precipitation, so that runoff decreases by 22%. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31 % in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34 % over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the southeast , however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27 % in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast , we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.

Fiber Reinforced Plastic (FRP) can be used for strengthening concrete or masonry constructions. One of the main problem in the use of FRP is the possible detachment of the reinforcement from the support material. This paper deals with the modeling of the FRP-concrete or masonry damage interface, accounting for the coupling occurring between the degradation of the cohesive material and the FRP detachment. To this end, a damage model is considered for the quasi-brittle material. In order to prevent strain localization and strong mesh sensitivity of the solution, an integral-type of nonlocal model based on the weighted spatial averaging of a strain-like quantity is developed. Regarding the interface, the damage is governed by the relative displacement occurring at bond. A suitable interface model which accounts for the mode I, mode II and mixed mode of damage is developed. The coupling between the body damage and the interface damage is performed computing the body damage on the bond surface. Numerical examples are presented.

International audience; The SAMM (Sea Atmosphere Mediterranean Model) has been developed to study the climate evolution of the Mediterranean and European regions for the 21st Century. SAMM is a new concept of AORCM (Atmosphere-Ocean Regional Climate Model), where a global atmosphere model is locally coupled with a regional ocean circulation model. It consists of the global spectral AGCM ARPEGE-Climate model, whose variable resolution is maximum in the Mediterranean region (50 km), which has been coupled to the Mediterranean Sea limited area OGCM OPAMED (10 km). A 140-year numerical experiment starting in 1960 was run with the AORCM. Up to year 2000, forcing was prescribed from observed values, whereas forcing following a SRES-A2 scenario was applied beyond 2000. In order to ensure the model stability, a simple monthly heat flux correction on air-sea exchanges was applied. The present-climate validation proves that the AORCM is comparable to the state-of-the-art European Atmosphere Regional Climate Models (ARCM) at the same resolution. At first order, the climate change impact over Europe simulated by the AORCM is comparable with ARCM simulations. However the AORCM significantly amplifies the climate change signal over large parts of Europe with respect to the corresponding ARCM: the warming is higher in all seasons and in many areas of Europe (up to 25% of the signal), winters are wetter over northern Europe and summers drier over southern and eastern Europe (up to 50% of the signal). These differences are highly significant and the choice between coupled and non-coupled regional models could be an additional source of uncertainty when evaluating the climate change response over Europe. The factors responsible for these differences are discussed. Among them, the response of the Mediterranean SST, better simulated by the high resolution Mediterranean Sea model of the AORCM, seems to be preponderant. Further mechanism studies and model inter-comparisons are however required to legitimate the present results.

In November 2011, an Atlantic depression affected the Mediterranean basin, eventually evolving into a Tropical-Like Cyclone (TLC or Mediterranean Hurricane, usually designated as Medicane). In the region affected by the Medicane, mean sea level pressures down to 990 hPa, wind speeds of hurricane intensity close to the eye (around 115 km/h) and intense rainfall in the prefrontal zone were reported. The intensity of this event, together with its long permanence over the sea, suggested its suitability as a paradigmatic case for investigating the sensitivity of a numerical modeling system to different configurations, air-sea interface parameterizations and coupling approaches. Toward this aim, a set of numerical experiments with different parameterization schemes and levels of coupling complexity was carried out within the Coupled Ocean Atmosphere Wave Sediment Transport System (COAWST), which allows the description of air-sea dynamics by coupling an atmospheric model (WRF), an ocean circulation model (ROMS), and a wave model (SWAN). The sensitivity to different initialization times and Planetary Boundary Layer (PBL) parameterizations was firstly investigated by running a set of WRF standalone (atmospheric-only) simulations. In order to better understand the effect of coupling on the TLC formation, intensification and trajectory, different configurations of atmosphere-ocean coupling were subsequently tested, eventually including the full coupling among atmosphere, ocean and waves, also changing the PBL parameterization and the formulation of the surface roughness. Results show a strong sensitivity of both the trajectory and the intensity of this TLC to the initial conditions, while the tracks and intensities provided by the coupled modeling approaches explored in this study do not introduce drastic modifications with respect to those resulting from a fine-tuned standalone atmospheric run, though they provide by definition a better physical and energetic consistency. Nevertheless; the use of different schemes for the calculation of the surface roughness from wave motion, which reflects the description of air-sea interface processes, can significantly affect the results in the fully coupled runs.

The ultimate aim of this thesis is to enhance our understanding of tidal wave propagation in convergent alluvial estuaries (of infinite length). In the process, a new analytical model has been developed as a function of externally defined dimensionless parameters describing friction, channel convergence and river discharge. This model has been used to investigate the potential influence of human interventions such as dredging, land reclamation, and freshwater withdrawal on tidal dynamics. The method allows to reproduce the most relevant features of the tidal wave (tidal amplitude, velocity amplitude, wave celerity and phase lag) along the estuary with a minimum requirement of information, such as geometrical data and the tidal forcing at the estuary mouth. Analytical solutions to the one-dimensional St. Venant equations for tidal hydrodynamics in convergent alluvial estuaries with negligible river discharge can be cast in the form of a set of four implicit dimensionless equations for phase lag, velocity amplitude, damping, and wave celerity, as a function of two localized parameters describing friction and convergence (dependent on tidal amplitude and depth). This method allows comparison of different analytical approaches by rewriting the different solutions in the same format. In this thesis, both classical and more recent formulations are compared, showing the differences and similarities in view of their specific simplifications. The envelope method that subtracts envelopes at high water and low water can be used to derive damping equations that use different friction approximations, resulting in as many analytical solutions, and thereby building one consistent theoretical framework. It is important to note that a multi-reach approach has to be adopted to follow variations of the estuarine amplitude and depth along the estuary by simple integration of the damping over a distance interval (e.g., 1 km), which is repeated for the entire length of the estuary. The asymptotic behaviour of tidal damping has also been investigated. A new asymptotic solution of the tidal amplitude has been found that reflects the balance between friction and channel convergence when the distance from the mouth approaches infinity. As a consequence, the usual assumption that the tidal amplitude and velocity amplitude along the estuary axis can be described by an exponential function appears only to be valid for an ideal or frictionless estuary. We also found that tidal amplification is increased with deepening until a maximum value is reached at a critical depth (corresponding to the maximum tidal amplitude). A further increase of depth reduces the tidal amplification until the frictionless standing wave system is reached asymptotically. The theoretical framework has subsequently been extended to take into account the effect of river discharge, which allows the analytical solutions to be applicable even in the upstream part of an estuary where the influence of river discharge is not negligible. It is observed that the residual water level slope resulting from asymmetric friction has substantial influence on tidal wave propagation when including the effect of river discharge. The application to the Modaomen and Yangtze estuaries indicates that the proposed model fits the observations with realistic roughness values upstream, while a model with negligible river discharge can be made to fit observations only with unrealistically high roughness values. The new hydrodynamics model is particularly useful in combination with a salt intrusion model because the coupling reduces the number of calibration parameters and subsequently strengthens the reliability of the salt intrusion model. The application in 6 Malaysian estuaries shows good correspondence between the computed tidal excursion with observed salinities. Conversely, if observed salinities are known, the hydraulic parameters (depth, friction) may possibly be estimated via an inverse model using observed tidal excursion and tidal amplitudes. In summary, the new framework for analytical solutions of the tidal hydrodynamics equations is more accurate than the explicit analytical model based on the Lorentz linearization. It has been expanded to include river discharge and the effect of variable depth, and it has been coupled with an analytical salt intrusion model. This analytical framework has been proved to perform well in a wide range of estuaries where it has direct value in allowing the assessment of the consequence of human interventions, such as by dredging or water abstractions. More importantly, it provides direct insight in cause-effect relations which are often nonlinear and it is a valuable educational tool to give insight into the inner functioning of a complex hydrodynamic system.

The continuous increase in atmospheric carbon dioxide (CO2) contributes to changes in plant evapotranspiration and terrestrial water budgets in two ways. Firstly, elevated CO2 can result in a water saving effect, since increasing CO2 reduces stomatal opening and therefore decreases transpiration. Secondly, CO2 fertilization increases biomass accumulation and leaf area at plant canopy level, likely increasing transpiration1. Vegetation and hydrological models can be used to investigate the CO2 response and the bidirectional effects outlined above, including their relative contribution to the changes in the water cycle. However, the intrinsic plant-soil interaction and the uncertainty related to model parameterization have rarely been considered.Hence, we coupled a detailed plant growth and soil hydrological model by using the generic model frameworks Plant growth Modelling Framework (PMF)2 and Catchment Modelling Framework (CMF)3. Up to date response mechanisms have been implemented in PMF to simulate the various ways of how plant physiology is influenced by elevated CO2. Both models interact by using the Python computer language. Applying the coupled PMF-CMF model we investigate the effects of elevated CO2 in a number of plant physiological and environmental variables such as biomass, leaf area index and soil moisture using field data of a long-term Free Air Carbon Enrichment (FACE) experiment in Giessen, Germany. In this experiment, various grassland varieties (herbs, legumes, grass) grow under elevated (+20%) and ambient CO2 since 1997.A Monte Carlo based uncertainty analysis (GLUE) is conducted to investigate the coupled PMF-CMF parameter space. The focus will be on the identification of parameters for plant and soil, which are the drivers for the CO2 response of the terrestrial water balance. We will present first results of the simulation of biomass accumulation and transpiration under ambient and elevated CO2 concentrations.

Hemodynamic parameters play an important role in aneurysm formation and growth. However, it is difficult to directly observe a rapidly growing de novo aneurysm in a patient. To investigate possible associations between hemodynamic parameters and the formation and growth of intracranial aneurysms, the present study constructed a computational model of a case with an internal carotid artery aneurysm and an anterior communicating artery aneurysm, based on the CT angiography findings of a patient. To simulate the formation of the anterior communicating artery aneurysm and the growth of the internal carotid artery aneurysm, we then constructed a model that virtually removed the anterior communicating artery aneurysm, and a further two models that also progressively decreased the size of the internal carotid artery aneurysm. Computational simulations of the fluid dynamics of the four models were performed under pulsatile flow conditions, and wall shear stress was compared among the different models. In the three aneurysm growth models, increasing size of the aneurysm was associated with an increased area of low wall shear stress, a significant decrease in wall shear stress at the dome of the aneurysm, and a significant change in the wall shear stress of the parent artery. The wall shear stress of the anterior communicating artery remained low, and was significantly lower than the wall shear stress at the bifurcation of the internal carotid artery or the bifurcation of the middle cerebral artery. After formation of the anterior communicating artery aneurysm, the wall shear stress at the dome of the internal carotid artery aneurysm increased significantly, and the wall shear stress in the upstream arteries also changed significantly. These findings indicate that low wall shear stress may be associated with the initiation and growth of aneurysms, and that aneurysm formation and growth may influence hemodynamic parameters in the local and adjacent arteries.

Strong offshore winds are frequently observed over the Gulf of Tehuantepec in the eastern Pacific Ocean when synoptic conditions create a cross-isthmus pressure gradient through the Chivela Pass in southern Mexico. During such high wind events, turbulent mixing and upwelling in the upper-ocean can reduce the sea-surface temperature by several degrees within hours of event onset. This research conducts an extensive analysis of aircraft measurements from the 2004 Gulf of Tehuantepec Experiment (GOTEX). Combined with coupled COAMPS/NCOM simulations, this research provides new insight into the spatial and temporal evolution of the marine and atmospheric boundary layers during outflow events. Three regions within the outflow are identified with distinct response characteristics. The addition of COAMPS simulations reveals the three-dimensional variations of the outflow jet not visible from the observations and the presence of a secondary outflow jet to the east that influences the symmetry of the atmospheric forcing. Calculations of the ocean mixed layer heat budget indicate entrainment mixing as the dominant cooling mechanism during outflow events. An evaluation of the fully-coupled model reveals minimal improvement in wind speed and stress, temperature, and moisture, but shows the greatest improvement in the air-sea temperature difference and surface sensible and latent heat fluxes. http://archive.org/details/evolutionofatmos1094517376 Lieutenant Commander, United States Navy Approved for public release; distribution is unlimited.

This paper proposes a more realistic mathematical simulation method to investigate the dynamic process of tumour angio-genesis by fully coupling the vessel growth, tumour growth and associated blood perfusion. The tumour growth and angiogenesis are coupled by the chemical microenvironment and the cell-matrix interaction. The haemodynamic calculation is carried out on the new vasculature, and an estimation of vessel collapse is made according to the wall shear stress criterion. The results are consistent with physiological observations, and further confirm the application of the coupled model feedback mechanism. The model is available to examine the interactions between angiogenesis and tumour growth, to study the change in the dynamic process of chemical environment and the vessel remodeling.

In the last years, the availability of new technologies of Earth Observation encouraged researches to use integrated approaches for environmental monitoring. Even for agro-hydrological applications, remotely sensed data are available on wide areas allowing the retrieval of cost-effective and representative estimation of high spatial and temporal variability of the soil-vegetation system variables. In particular, soil water content plays an important role determining the partition of precipitation between surface runoff and infiltration and, moreover, influences the distribution of the incoming radiation between latent and sensible heat flux. As a consequence, distributed soil water content maps are essential data for watershed applications such as flood prediction and crop irrigation scheduling. Since cloud cover has been highlighted as the main limitation of SW/TIR traditional techniques, this research is focused on the applicability of soil moisture models based on active microwave. In particular, a Semi Empirical Coupled Model (SECM) is proposed. Reliable assessments of both surface roughness and dielectric constant (thus soil moisture) are retrieved by means of two iterative modules, without any calibration phase. The validation with in situ soil moisture, taken at a depth comparable to the RADAR penetration, gives a good agreement for bare-sparse vegetation coverage. The research is carried out on the 24 km² test-site of DEMMIN (Gormin farm, Mecklenburg Vorpommern), in the North-East of Germany. Data were acquired within the ESA-funded AgriSAR project, between April and July 2006. The implemented model uses HH, VV and HV polarized L-bands, acquired by the German Aerospace Center (Deutsches Zentrum fur Luft- und Raumfahrt - DLR) using an airborne platform.

A regional coupled atmosphere-ocean model was developed to study the role of air-sea interactions in the simulation of the Indian summer monsoon. The coupled model includes the regional climate model (RegCM3) as atmospheric component and the regional ocean modeling system (ROMS) as oceanic component. The two-way coupled model system exchanges sea surface temperature (SST) from the ocean to the atmospheric model and surface wind stress and energy fluxes from the atmosphere to the ocean model. The coupled model is run for four years 1997, 1998, 2002 and 2003 and the results are compared with observations and atmosphere-only model runs employing Reynolds SSTs as lower boundary condition. It is found that the coupled model captures the main features of the Indian monsoon and simulates a substantially more realistic spatial and temporal distribution of monsoon rainfall compared to the uncoupled atmosphere-only model. The intraseasonal oscillations are also better simulated in the coupled model compared to the atmosphere-only model. These improvements are due to a better representation of the feedbacks between the SST and convection and highlight the importance of air-sea coupling in the simulation of the Indian monsoon. © Springer-Verlag 2008.

6 pages, 3 figures, 1 table, supporting information http://onlinelibrary.wiley.com/doi/10.1029/2008GL036568/suppinfo, El Niño-Southern Oscillation (ENSO) properties can be modulated by many factors; most previous studies have focused on physical aspects of the climate system in the tropical Pacific. Ocean biology-induced feedback (OBF) onto physics and bio-climate coupling have been the subject of much recent interest, revealing striking model dependence and even conflicting results. Current satellite data are able to resolve the space-time structure of oceanic signals both in biology and physics, providing an opportunity for quantifying their relationships. Here we use the biological signature from satellite ocean color data to estimate interannual variability of the attenuation depth of solar radiation (Hp), a field linking ocean biology and physics. We then apply a singular value decomposition (SVD) analysis to interannual Hp and sea surface temperature (SST) anomaly fields to derive an empirical Hp model which is incorporated in a hybrid coupled ocean-atmosphere model of the tropical Pacific to represent the OBF. It is shown that the OBF can have significant effects on ENSO behaviors, including its amplitude, oscillation periods and seasonal phase locking, This research is supported in part by a NSF grant (ATM-0727668) and NASA grants (NCC5374, NAG512246, NNX08AI74G, NNX08AI76G and NNX08AT50G). J. Ballabrera-Poy is supported by a Ramón y Cajal contract from the Spanish Ministry of Science and Innovation and D. Chen is supported by the National Natural Science Foundation of China under contract No 40730843 and the National Basic Research Program of China under contract No 2007CB816005