| publications-1611 |
PEER REVIEWED ARTICLE |
2017 |
Rene Orth , Emanuel Dutra , Isabel F. Trigo , Gianpaolo Balsamo |
Advancing land surface model development with satellite-based Earth observations |
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10.5194/hess-21-2483-2017 |
Uncategorized |
Wastewater Treatment Plants |
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Abstract. The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts, we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability, and understanding of climate system feedbacks. |
603608 |
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| publications-1612 |
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2017 |
Martin Wegmann , Yvan Orsolini , Emanuel Dutra , Olga Bulygina , Alexander Sterin , Stefan Brönnimann |
Eurasian snow depth in long-term climate reanalyses |
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10.5194/tc-11-923-2017 |
Uncategorized |
Wastewater Treatment Plants |
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Abstract. Snow cover variability has significant effects on local and global climate evolution. By changing surface energy fluxes and hydrological conditions, changes in snow cover can alter atmospheric circulation and lead to remote climate effects. To document such multi-scale climate effects, atmospheric reanalysis and derived products offer the opportunity to analyze snow variability in great detail far back to the early 20th century. So far only little is know about their quality. Comparing snow depth in four long-term reanalysis datasets with Russian in situ snow depth data, we find a moderately high daily correlation (around 0.6–0.7), which is comparable to correlations for the recent era (1981–2010), and a good representation of sub-decadal variability. However, the representation of pre-1950 inter-decadal snow variability is questionable, since reanalysis products divert towards different base states. Limited availability of independent long-term snow data makes it difficult to assess the exact cause for this bifurcation in snow states, but initial investigations point towards representation of the atmosphere rather than differences in assimilated data or snow schemes. This study demonstrates the ability of long-term reanalysis to reproduce snow variability accordingly. |
603608 |
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| publications-1613 |
PEER REVIEWED ARTICLE |
2017 |
Anton Beljaars , Emanuel Dutra , Gianpaolo Balsamo , Florian Lemarié |
On the numerical stability of surface–atmosphere coupling in weather and climate models |
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10.5194/gmd-10-977-2017 |
IoT & Sensors |
Groundwater |
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Abstract. Coupling the atmosphere with the underlying surface presents numerical stability challenges in cost-effective model integrations used for operational weather prediction or climate simulations. These are due to the choice of large integration time steps compared to the physical timescale of the problem, aiming at reducing computational burden, and to an explicit flux coupling formulation, often preferred for its simplicity and modularity. Atmospheric models therefore use the surface-layer temperatures (representative of the uppermost soil, snow, ice, water, etc.) at the previous integration time step in all surface–atmosphere heat-flux calculations and prescribe fluxes to be used in the surface model integrations. Although both models may use implicit formulations for the time steps, the explicit flux coupling can still lead to instabilities.In this study, idealized simulations with a fully coupled implicit system are performed to derive an empirical relation between surface heat flux and surface temperature at the new time level. Such a relation mimics the fully implicit formulation by allowing one to estimate the surface temperature at the new time level without solving the surface heat diffusion problem. It is based on similarity reasoning and applies to any medium with constant heat diffusion and heat capacity parameters. The advantage is that modularity of the code is maintained and that the heat flux can be computed in the atmospheric model in such a way that instabilities in the snow or ice code are avoided. Applicability to snow–ice–soil models with variable density is discussed, and the loss of accuracy turns out to be small. A formal stability analysis confirms that the parametrized implicit-flux coupling is unconditionally stable. |
603608 |
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| publications-1614 |
PEER REVIEWED ARTICLE |
2017 |
Adam S. Candy |
An implicit wetting and drying approach for non-hydrostatic baroclinic flows in high aspect ratio domains |
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10.1016/j.advwatres.2017.02.004 |
Data Management & Analytics |
Groundwater |
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No abstract available |
603663 |
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| publications-1615 |
PEER REVIEWED ARTICLE |
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Makropoulos, Christos |
A risk reduction framework towards extreme and rare events in coastal regions: the case study of Rethymno, Crete |
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Simulation & Modeling |
Groundwater |
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No abstract available |
603663 |
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| publications-1616 |
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No year available |
Doong, D.J. |
Statistical Analysis on the Long-term Observations of Typhoon Waves in the Taiwan Sea |
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10.6119/jmst-015-0610-7 |
Simulation & Modeling |
Groundwater |
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No abstract available |
603663 |
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| publications-1617 |
PEER REVIEWED ARTICLE |
2015 |
A. Vire , J. Xiang , C. C. Pain |
An immersed-shell method for modelling fluid-structure interactions |
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10.1098/rsta.2014.0085 |
IoT & Sensors |
Groundwater |
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The paper presents a novel method for numerically modelling fluid–structure interactions. The method consists of solving the fluid-dynamics equations on an extended domain, where the computational mesh covers both fluid and solid structures. The fluid and solid velocities are relaxed to one another through a penalty force. The latter acts on a thin shell surrounding the solid structures. Additionally, the shell is represented on the extended domain by a non-zero shell-concentration field, which is obtained by conservatively mapping the shell mesh onto the extended mesh. The paper outlines the theory underpinning this novel method, referred to as the immersed-shell approach. It also shows how the coupling between a fluid- and a structural-dynamics solver is achieved. At this stage, results are shown for cases of fundamental interest. |
603663 |
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| publications-1618 |
PEER REVIEWED ARTICLE |
2015 |
J. Zheng , J. Zhu , Z. Wang , F. Fang , C. C. Pain , J. Xiang |
Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9) |
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10.5194/gmd-8-3421-2015 |
IoT & Sensors |
Groundwater |
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Abstract. An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection–diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively. |
603663 |
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| publications-1619 |
PEER REVIEWED ARTICLE |
2016 |
D. Xiao , P. Yang , F. Fang , J. Xiang , C.C. Pain , I.M. Navon |
Non-intrusive reduced order modelling of fluid–structure interactions |
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10.1016/j.cma.2015.12.029 |
Simulation & Modeling |
Groundwater |
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No abstract available |
603663 |
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| publications-1620 |
PEER REVIEWED ARTICLE |
2016 |
A. Viré , J. Spinneken , M.D. Piggott , C.C. Pain , S.C. Kramer |
Application of the immersed-body method to simulate wave–structure interactions |
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10.1016/j.euromechflu.2015.10.001 |
IoT & Sensors |
Groundwater |
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No abstract available |
603663 |
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