Coupling of the regional climate model COSMO-CLM using OASIS3-MCT with regional ocean, land surface or global atmosphere model: description and performance

Abstract. We present the prototype of a regional climate system model based on the COSMO-CLM regional climate model coupled with several model components, analyze the performance of the couplings and present a strategy to find an optimum configuration with respect to computational costs and time to solution. The OASIS3-MCT coupler is used to couple COSMO-CLM with two land surface models (CLM and VEG3D), a regional ocean model for the Mediterranean Sea (NEMO-MED12), two ocean models for the North and Baltic Sea (NEMO-NORDIC and TRIMNP+CICE) and the atmospheric component of an earth system model (MPI-ESM). We present a unified OASIS3-MCT interface which handles all couplings in a similar way, minimizes the model source code modifications and describes the physics and numerics of the couplings. Furthermore, we discuss solutions for specific regional coupling problems like handling of different domains, multiple usage of MCT interpolation library and efficient exchange of 3D fields. A series of real-case simulations over Europe has been conducted and the computational performance of the couplings has been analyzed. The usage of the LUCIA tool of the OASIS3-MCT coupler enabled separation of the direct costs of: coupling, load imbalance and additional computations. The resulting limits for time to solution and costs are shown and the potential of further improvement of the computational efficiency is summarized for each coupling. It was found that the OASIS3-MCT coupler keeps the direct coupling costs of communication and horizontal interpolation small in comparison with the costs of the additional computations and load imbalance for all investigated couplings. For the first time this could be demonstrated for an exchange of approximately 450 2D fields per time step necessary for the atmosphere-atmosphere coupling between COSMO-CLM and MPI-ESM. A procedure for finding an optimum configuration for each of the couplings was developed considering the time to solution and costs of the simulations. The optimum configurations are presented for sequential and concurrent coupling layouts. The procedure applied can be regarded as independent on the specific coupling layout and coupling details.

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The COSMO-CLM 4.8 regional climate model coupled to regional ocean, land surface and global earth system models using OASIS3-MCT: description and performance

Geoscientific Model Development ◽

10.5194/gmd-10-1549-2017 ◽

2017 ◽

Vol 10 (4) ◽

pp. 1549-1586 ◽

Cited By ~ 15

Author(s):

Andreas Will ◽

Naveed Akhtar ◽

Jennifer Brauch ◽

Marcus Breil ◽

Edouard Davin ◽

...

Keyword(s):

Regional Climate Model ◽

Direct Cost ◽

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Ocean Model ◽

Earth System ◽

Climate System Model ◽

Community Land Model ◽

Computational Performance

Abstract. We developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (the Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic seas (NEMO-NORDIC and TRIMNP+CICE) and the MPI-ESM Earth system model.We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimising the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of the MCT library and exchange of 3-D fields.We analyse and compare the computational performance of the different couplings based on real-case simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand-alone mode and (5) residual cost including i.a. CCLM additional computations.Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in OASIS3-MCT remains below 7 % of the CCLM stand-alone cost for all couplings investigated. This is in particular true for the exchange of 450 2-D fields between CCLM and MPI-ESM. We identified remaining limitations in the coupling strategies and discuss possible future improvements of the computational efficiency.

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A multivariate comparison of two land-surface models integrated into an Arctic Regional Climate System model

Annals of Glaciology ◽

10.3189/s0260305500013914 ◽

1997 ◽

Vol 25 ◽

pp. 127-131

Author(s):

Amanda Lynch ◽

David McGinnis ◽

William L. Chapman ◽

Jeffrey S. Tilley

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Climate System ◽

System Model ◽

Small Scale ◽

Land Surface Models ◽

Climate System Model ◽

Surface Models

Different vegetation models impact the atmospheric response of a regional climate model in different ways, and hence have an impact upon the ability of that model to match an observed climatology. Using a multivariate principal-component analysis, we investigate the relationships between several land-surface models (BATS, LSM) coupled to a regional climate model, and observed climate parameters over the North Slope of Alaska. In this application, annual cycle simulations at 20 km spatial resolution are compared with European Centre for Medium-Range Weather Forecasts (ECMWF) climatology. Initial results demonstrate broad agreement between all models; however, small-scale regional variations between land-surface models indicate the strengths and weaknesses of the land-surface treatments in a climate system model. Specifically, we found that the greater surface-moisture availability and temperature-dependent albedo formulation of the LSM model allow for a higher proportion of low-level cloud, and a later, more rapid transition from the winter to the summer regime. Crucial to this transition is the seasonal cycle of incoming solar radiation. These preliminary results indicate the importance of the land-surface hydrologic cycle in modelling the seasonal transitions.

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A multivariate comparison of two land-surface models integrated into an Arctic Regional Climate System model

Annals of Glaciology ◽

10.1017/s0260305500013914 ◽

1997 ◽

Vol 25 ◽

pp. 127-131

Author(s):

Amanda Lynch ◽

David McGinnis ◽

William L. Chapman ◽

Jeffrey S. Tilley

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Climate System ◽

System Model ◽

Small Scale ◽

Land Surface Models ◽

Climate System Model ◽

Surface Models

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Referee comment: Coupling of the regional climate model COSMO-CLM using OASIS3-MCT with regional ocean, land surface or global atmosphere model: description and performance

10.5194/gmd-2016-47-rc2 ◽

2016 ◽

Author(s):

Sophie Valcke

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Model Description ◽

Atmosphere Model ◽

And Performance

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Executive Editor Comment on "Coupling of the regional climate model COSMO-CLM using OASIS3-MCT with regional ocean, land surface or global atmosphere model: description and performance"

10.5194/gmd-2016-47-sc1 ◽

2016 ◽

Author(s):

Astrid Kerkweg

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Model Description ◽

Editor Comment ◽

Executive Editor ◽

Atmosphere Model ◽

And Performance

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Evaluation of Temperature Simulation over Northern Thailand from Regional Climate Model Coupled with Land Surface Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.866.108 ◽

2017 ◽

Vol 866 ◽

pp. 108-111

Author(s):

Theerapan Saesong ◽

Pakpoom Ratjiranukool ◽

Sujittra Ratjiranukool

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Global Analysis ◽

Regional Climate ◽

Land Surface Model ◽

Analysis Data ◽

Surface Model ◽

Northern Thailand ◽

Weather Model

Numerical Weather Model called The Weather Research and Forecasting model, WRF, developed by National Center for Atmospheric Research (NCAR) is adapted to be regional climate model. The model is run to perform the daily mean air surface temperatures over northern Thailand in 2010. Boundery dataset provided by National Centers for Environmental Prediction, NCEP FNL, (Final) Operational Global Analysis data which are on 10 x 10. The simulated temperatures by WRF with four land surface options, i.e., no land surface scheme (option 0), thermal diffusion (option 1), Noah land-surface (option 2) and RUC land-surface (option 3) were compared against observational data from Thai Meteorological Department (TMD). Preliminary analysis indicated WRF simulations with Noah scheme were able to reproduce the most reliable daily mean temperatures over northern Thailand.

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Precipitation Simulations Using WRF as a Nested Regional Climate Model

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2186.1 ◽

2009 ◽

Vol 48 (10) ◽

pp. 2152-2159 ◽

Cited By ~ 93

Author(s):

Melissa S. Bukovsky ◽

David J. Karoly

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Model Simulation ◽

Regional Climate ◽

Warm Season ◽

Weather Forecast ◽

Weather Research And Forecasting ◽

Model Setup ◽

Environmental Prediction

Abstract This note examines the sensitivity of simulated U.S. warm-season precipitation in the Weather Research and Forecasting model (WRF), used as a nested regional climate model, to variations in model setup. Numerous options have been tested and a few of the more interesting and unexpected sensitivities are documented here. Specifically, the impacts of changes in convective and land surface parameterizations, nest feedbacks, sea surface temperature, and WRF version on mean precipitation are evaluated in 4-month-long simulations. Running the model over an entire season has brought to light some issues that are not otherwise apparent in shorter, weather forecast–type simulations, emphasizing the need for careful scrutiny of output from any model simulation. After substantial testing, a reasonable model setup was found that produced a definite improvement in the climatological characteristics of precipitation over that from the National Centers for Environmental Prediction–National Center for Atmospheric Research global reanalysis, the dataset used for WRF initial and boundary conditions in this analysis.

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A Highly Resolved Regional Climate Model (IPRC-RegCM) and Its Simulation of the 1998 Severe Precipitation Event over China. Part I: Model Description and Verification of Simulation*

Journal of Climate ◽

10.1175/1520-0442(2003)016<1721:ahrrcm>2.0.co;2 ◽

2003 ◽

Vol 16 (11) ◽

pp. 1721-1738 ◽

Cited By ~ 155

Author(s):

Yuqing Wang ◽

Omer L. Sen ◽

Bin Wang

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Precipitation Event ◽

Model Description

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New lessons on the Sudd hydrology learned from remote sensing and climate modeling

Hydrology and Earth System Sciences ◽

10.5194/hess-10-507-2006 ◽

2006 ◽

Vol 10 (4) ◽

pp. 507-518 ◽

Cited By ~ 28

Author(s):

Y. A. Mohamed ◽

H. H. G. Savenije ◽

W. G. M. Bastiaanssen ◽

B. J .J. M. van den Hurk

Keyword(s):

Remote Sensing ◽

Regional Climate Model ◽

Land Surface ◽

Evaporation Rate ◽

Climate Model ◽

Regional Climate ◽

Remote Sensing Data ◽

Open Water ◽

Groundwater Table ◽

Water Evaporation

Abstract. Despite its local and regional importance, hydro-meteorological data on the Sudd (one of Africa's largest wetlands) is very scanty. This is due to the physical and political situation of this area of Sudan. The areal size of the wetland, the evaporation rate, and the influence on the micro and meso climate are still unresolved questions of the Sudd hydrology. The evaporation flux from the Sudd wetland has been estimated using thermal infrared remote sensing data and a parameterization of the surface energy balance (SEBAL model). It is concluded that the actual spatially averaged evaporation from the Sudd wetland over 3 years of different hydrometeorological characteristics varies between 1460 and 1935 mm/yr. This is substantially less than open water evaporation. The wetland area appears to be 70% larger than previously assumed when the Sudd was considered as an open water body. The temporal analysis of the Sudd evaporation demonstrated that the variation of the atmospheric demand in combination with the inter-annual fluctuation of the groundwater table results into a quasi-constant evaporation rate in the Sudd, while open water evaporation depicts a clear seasonal variability. The groundwater table characterizes a distinct seasonality, confirming that substantial parts of the Sudd are seasonal swamps. The new set of spatially distributed evaporation parameters from remote sensing form an important dataset for calibrating a regional climate model enclosing the Nile Basin. The Regional Atmospheric Climate Model (RACMO) provides an insight not only into the temporal evolution of the hydro-climatological parameters, but also into the land surface climate interactions and embedded feedbacks. The impact of the flooding of the Sudd on the Nile hydroclimatology has been analysed by simulating two land surface scenarios (with and without the Sudd wetland). The paper presents some of the model results addressing the Sudd's influence on rainfall, evaporation and runoff of the river Nile, as well as the influence on the microclimate. The paper presents a case study that confirms the feasibility of using remote sensing data (with good spatial and poor temporal coverage) in conjunction with a regional climate model. The combined model provides good temporal and spatial representation in a region characterized by extremely scarce ground data.

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