OR/14/022 Description of dynamic (run-time) approaches - Revision history

Ajhil: /* ESMF */

2022-07-01T12:53:07Z

ESMF

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	ESMF is based on two types of components: 'Gridded Components' (ESMF_GridComp) and 'Coupler Components' (ESMF_CplComp) (ESMF 2013<ref name="ESMF"></ref>). Gridded Components represent the physical domain being modelled while Coupler Components enable data transformation and transfer (ESMF 2013<ref name="ESMF"></ref>). Coupler Component's operations include: time advancement, data redistribution, spectral and grid transformations, time averaging, and unit conversions (ESMF 2013<ref name="ESMF"></ref>). Coupler Components need to be written in Fortran on case by case basis using ESMF classes (ESMF 2013<ref name="ESMF"></ref>). Gridded Components need to be split into one or more initialise, run, and finalise sections callable as subroutines (Goodall et al., 2013<ref name="Goodall 2013"></ref>, ESMF 2013<ref name="ESMF"></ref>). ESMF allow for nested components, with "progressively more specialised processes or refined grids" (ESMF 2013<ref name="ESMF"></ref>).		ESMF is based on two types of components: 'Gridded Components' (ESMF_GridComp) and 'Coupler Components' (ESMF_CplComp) (ESMF 2013<ref name="ESMF"></ref>). Gridded Components represent the physical domain being modelled while Coupler Components enable data transformation and transfer (ESMF 2013<ref name="ESMF"></ref>). Coupler Component's operations include: time advancement, data redistribution, spectral and grid transformations, time averaging, and unit conversions (ESMF 2013<ref name="ESMF"></ref>). Coupler Components need to be written in Fortran on case by case basis using ESMF classes (ESMF 2013<ref name="ESMF"></ref>). Gridded Components need to be split into one or more initialise, run, and finalise sections callable as subroutines (Goodall et al., 2013<ref name="Goodall 2013"></ref>, ESMF 2013<ref name="ESMF"></ref>). ESMF allow for nested components, with "progressively more specialised processes or refined grids" (ESMF 2013<ref name="ESMF"></ref>).

	The user is required to write a wrapper code that will connect component's native data structures to ESMF data structures (ESMF 2013<ref name="ESMF"></ref>). There are two ways to do it: either using the 'ESMF_Array' class to represent the data structures in an index-space, or using the 'ESMF_Field' class to represent them it in a physical space (ESMF 2013<ref name="ESMF"></ref>). In the latter case interpolation weights can be calculated using coordinate information stored in the 'ESMF_Grid' class; bilinear and higher order interpolation calculations in up to three dimensions are supported (ESMF 2013<ref name="ESMF"></ref>). User is also required to write 'SetServices' routine, which associates the ESMF initialise/run/finalise methods with their corresponding user code methods (ESMF 2013<ref name="ESMF"></ref>).		The user is required to write a wrapper code that will connect component's native data structures to ESMF data structures (ESMF 2013<ref name="ESMF"></ref>). There are two ways to do it: either using the 'ESMF_Array' class to represent the data structures in an index-space, or using the 'ESMF_Field' class to represent them it in a physical space (ESMF 2013<ref name="ESMF"></ref>). In the latter case interpolation weights can be calculated using coordinate information stored in the 'ESMF_Grid' class; bilinear and higher order interpolation calculations in up to three dimensions are supported (ESMF 2013<ref name="ESMF"></ref>). User is also required to write 'SetServices' routine, which associates the ESMF initialise/run/finalise methods with their corresponding user code methods (ESMF 2013<ref name="ESMF">ESMF 2013. ''Earth System Modeling Framework Website'' [Online]. [cited 14 November 2013]. Available: http://www.earthsystemmodeling.org/</ref>).

	Data is passed using container classes called 'States' (Goodall et al., 2013<ref name="Goodall 2013"></ref>); each Gridded component has an import State, containing its inputs, and an export State, containing its outputs (ESMF 2013<ref name="ESMF"></ref>). States can hold different data classes, including Arrays, ArrayBundles, Fields, or FieldBundles (ESMF 2013). ‘Arrays store multidimensional data associated with an index space. Fields include data Arrays along with an associated physical grid and a decomposition that specifies how data points in the physical grid are distributed across computing resources. ArrayBundles and FieldBundles are groupings of Arrays and Fields, respectively’ (Goodall et al., 2013<ref name="Goodall 2013"></ref>).		Data is passed using container classes called 'States' (Goodall et al., 2013<ref name="Goodall 2013"></ref>); each Gridded component has an import State, containing its inputs, and an export State, containing its outputs (ESMF 2013<ref name="ESMF"></ref>). States can hold different data classes, including Arrays, ArrayBundles, Fields, or FieldBundles (ESMF 2013<ref name="ESMF 2013"></ref>). ‘Arrays store multidimensional data associated with an index space. Fields include data Arrays along with an associated physical grid and a decomposition that specifies how data points in the physical grid are distributed across computing resources. ArrayBundles and FieldBundles are groupings of Arrays and Fields, respectively’ (Goodall et al., 2013<ref name="Goodall 2013"></ref>).

	Although, ESMF is primarily aimed at high performance climate/weather/atmospheric computations, its developers seek cooperation with hydrological modellers and have been looking into ways to achieve cross-domain integration between ESMF and water resources modelling systems (Deluca et al., 2008<ref name="Deluca">DELUCA, C, OEHMKE, R, NECKELS, D, THEURICH, G, O'KUINGHTTONS, R, DE FAINCHTEIN, R, MURPHY, S and DUNLAP, R. Enhancements for Hydrological Modeling in ESMF. American Geophysical Union Fall Meeting 2008. </ref>).		Although, ESMF is primarily aimed at high performance climate/weather/atmospheric computations, its developers seek cooperation with hydrological modellers and have been looking into ways to achieve cross-domain integration between ESMF and water resources modelling systems (Deluca et al., 2008<ref name="Deluca">DELUCA, C, OEHMKE, R, NECKELS, D, THEURICH, G, O'KUINGHTTONS, R, DE FAINCHTEIN, R, MURPHY, S and DUNLAP, R. Enhancements for Hydrological Modeling in ESMF. American Geophysical Union Fall Meeting 2008. </ref>).

Ajhil: /* Time */

2022-07-01T12:50:35Z

Time

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	====Time====		====Time====
	The Invisible Modelling Environment (TIME) is a metadata-based framework developed within the Catchment Modelling Toolkit project in the Cooperative Research Centre for Catchment Hydrology (CRCCH) (Rahman et al., 2003<ref name="Rahman">RAHMAN, J M, SEATON, S P, PERRAUD, J-M., HOTHAM, H, VERRELLI, D I and COLEMAN, J R. It's TIME for a New Environmental Modelling Framework. Proceedings of MODSIM International Congress on Modelling and Simulation 2003 Townsville, Australia. ''Modelling and Simulation Society of Australia and New Zealand Inc''., 1727–1732. </ref>). CRCCH is currently a part of the eWater Cooperative Research Centre (CRC) — an organisation responsible for implementation of the Australian Government's National Hydrological Modelling Strategy (eWater CRC 2013).		The Invisible Modelling Environment (TIME) is a metadata-based framework developed within the Catchment Modelling Toolkit project in the Cooperative Research Centre for Catchment Hydrology (CRCCH) (Rahman et al., 2003<ref name="Rahman">RAHMAN, J M, SEATON, S P, PERRAUD, J-M., HOTHAM, H, VERRELLI, D I and COLEMAN, J R. It's TIME for a New Environmental Modelling Framework. Proceedings of MODSIM International Congress on Modelling and Simulation 2003 Townsville, Australia. ''Modelling and Simulation Society of Australia and New Zealand Inc''., 1727–1732. </ref>). CRCCH is currently a part of the eWater Cooperative Research Centre (CRC) — an organisation responsible for implementation of the Australian Government's National Hydrological Modelling Strategy (eWater CRC 2013<ref name="eWater 2013">eWater CRC 2013. eWater Cooperative Research Centre Website [Online]. Available: http://www.ewater.com.au/ [cited 2/12/2013].</ref>).

	TIME architecture is based on as a number of interacting layers, with each layer consisting of a number of components and a framework supporting the specific layer's function (Rahman et al., 2003<ref name="Rahman"></ref>). The central layer is the Kernel, which contains definitions of metadata tags, the parent classes for models and data, and mechanisms for performing IO operations (Rahman et al., 2003<ref name="Rahman"></ref>). The other layers include: the Model layer, which consists of all the modelling components; the Tools layer, which includes components for data and model processing and parameter optimisation; and the Visualisation and User Interface layer, which contains tools for data visualisation and user interaction (Rahman et al., 2003<ref name="Rahman"></ref>).		TIME architecture is based on as a number of interacting layers, with each layer consisting of a number of components and a framework supporting the specific layer's function (Rahman et al., 2003<ref name="Rahman"></ref>). The central layer is the Kernel, which contains definitions of metadata tags, the parent classes for models and data, and mechanisms for performing IO operations (Rahman et al., 2003<ref name="Rahman"></ref>). The other layers include: the Model layer, which consists of all the modelling components; the Tools layer, which includes components for data and model processing and parameter optimisation; and the Visualisation and User Interface layer, which contains tools for data visualisation and user interaction (Rahman et al., 2003<ref name="Rahman"></ref>).

Ajhil: /* Overview */

2022-07-01T12:47:14Z

Overview

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	===OASIS3-MCT_2.0 (Framework and Coupler) ===		===OASIS3-MCT_2.0 (Framework and Coupler) ===
	====Overview====		====Overview====
	The framework description for OASIS3-MCT_2.0 is modified from Valcke et al., (2013)<ref name="Valcke 2013">VALCKE, S, CRAIG, T, and COQUART, L. 2013. OASIS3-MCT User Guide, OASIS3-MCT 2.0, Technical Report, TR/CMGC/13/17, CERFACS/CNRS SUC URA No 1875, Toulouse, France. </ref>. In 1991, CERFACS started the development of a software interface to couple existing ocean and atmosphere numerical General Circulation Models. OASIS3-MCT_2.0 is interfaced with the MCT, developed by the Argonne National Laboratory in the USA. MCT implements fully parallel re-gridding and parallel distributed exchanges of the coupling fields based on pre- computed re-gridding weights and addresses. MCT has proven parallel performance and is also the underlying coupling software used in the CESM.		The framework description for OASIS3-MCT_2.0 is modified from Valcke et al., (2013)<ref name="Valcke 2013">VALCKE, S, CRAIG, T, and COQUART, L. 2013. OASIS3-MCT User Guide, OASIS3-MCT 2.0, Technical Report, TR/CMGC/13/17, CERFACS/CNRS SUC URA No 1875, Toulouse, France. </ref>. In 1991, CERFACS started the development of a software interface to couple existing ocean and atmosphere numerical General Circulation Models. OASIS3-MCT_2.0 is interfaced with the MCT, developed by the Argonne National Laboratory in the USA. MCT implements fully parallel re-gridding and parallel distributed exchanges of the coupling fields based on pre-computed re-gridding weights and addresses. MCT has proven parallel performance and is also the underlying coupling software used in the CESM.

	Low model component intrusiveness, portability and flexibility were key concepts when designing OASIS3-MCT_2.0. The software itself may be envisaged as a coupling library that needs to be linked to the component models, the main function of which is to interpolate and exchange the coupling fields between them to form a coupled system. OASIS3-MCT_2.0 supports coupling of 2D logically-rectangular fields but 3D fields and 1D fields expressed on unstructured grids are also supported using a one dimension degeneration of the structures.		Low model component intrusiveness, portability and flexibility were key concepts when designing OASIS3-MCT_2.0. The software itself may be envisaged as a coupling library that needs to be linked to the component models, the main function of which is to interpolate and exchange the coupling fields between them to form a coupled system. OASIS3-MCT_2.0 supports coupling of 2D logically-rectangular fields but 3D fields and 1D fields expressed on unstructured grids are also supported using a one dimension degeneration of the structures.

Ajhil: /* Web services */

2022-07-01T09:43:40Z

Web services

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	Another technology that could potentially be harnessed for building decision support systems is cloud computing. Environmental Virtual Observatory (EVO) pilot project, sponsored by the UK’s Natural Environment Research Council (NERC), employs cloud computing to integrate datasets, models and tools for cost-effective, efficient and transparent environmental monitoring and decision making (EVO 2013<ref name="EVO">EVO 2013. ''Environmental Virtual Observatory Website ''[Online]. [cited 14 November 2013]. Available: [http://www.evo-uk.org/ http://www.evo-uk.org/.]</ref>). EVO works with other international partners (e.g.: CUAHSI, NeON) to develop consistent standards for exchanging data and models (EVO 2013<ref name="EVO"></ref>). The project activities include developing cyber infrastructure, cloud-enabled environmental models, and a number of exemplar web-based services concerning soil and water management at both local and national scales (EVO 2013<ref name="EVO"></ref>). Exemplars developed within the course of the two year pilot project focus on a range of environmental problems, which directly affect the well-being of people in the UK, e.g.: studying national-scale nutrient fate using linked hydrogeological and biochemical models, developing a system to assess the effects of different land management practices on reducing diffuse pollution from agriculture, advancing modelling capabilities for drought and flood predictions to address and mitigate the effects of climate change, or establishing technologies for studying biodiversity and ecosystem service sustainability (EVO 2013<ref name="EVO"></ref>). EVO aims to provide different groups of users, from scientists to local stakeholders, with free and easy access to expert knowledge by combining assets from various sources with novel tools for data analysis and visualisation (Gurney et al., 2011<ref name="Gurney">GURNEY, R, EMMETT, B, MCDONALD, A, BLAIR, G, BUYTAERT, W, FREER, J E, HAYGARTH, P, REES, G, TETZLAFF, D and EVO SCIENCE TEAM. The Environmental Virtual Observatory: A New Vision for Catchment Science. American Geophysical Union Fall Meeting 2011. </ref>). The system is designed to promote feedback, ownership, community involvement, and better communication between technical ad non-technical users (EVO 2013<ref name="EVO"></ref>). An example of a community tool established within EVO is The Local Landscape Visualisation Tool, developed by engaging stakeholders in three catchments in the UK: the Afon Dyfi, the River Tarland, and the River Eden (Wilkinson et al., 2013<ref name="Wilkinson">WILKINSON, M, BEVEN, K, BREWER, P, EL-KHATIB, Y, GEMMELL, A, HAYGARTH, P, MACKAY, E, MACKLIN, M, MARSHALL, K, QUINN, P, STUTTER, M., THOMAS, N & VITOLO, C. The Environmental Virtual Observatory (EVO) local exemplar: A cloud based local landscape learning visualisation tool for communicating flood risk to catchment stakeholders. EGU General Assembly 2013 Vienna Austria. </ref>). The tool is accessed via a web portal and communicates flood risk in the local impacted communities. It is based on a number of services, i.e.: catchment datasets, hydrological models, and visualisation tools. Users can access real time data concerning river levels, rainfall, weather, and water quality, which is additionally supported by webcam images, or can use cloud-based models to explore how different land management strategies might affect the risk of flooding (Wilkinson et al., 2013<ref name="Wilkinson"></ref>).		Another technology that could potentially be harnessed for building decision support systems is cloud computing. Environmental Virtual Observatory (EVO) pilot project, sponsored by the UK’s Natural Environment Research Council (NERC), employs cloud computing to integrate datasets, models and tools for cost-effective, efficient and transparent environmental monitoring and decision making (EVO 2013<ref name="EVO">EVO 2013. ''Environmental Virtual Observatory Website ''[Online]. [cited 14 November 2013]. Available: [http://www.evo-uk.org/ http://www.evo-uk.org/.]</ref>). EVO works with other international partners (e.g.: CUAHSI, NeON) to develop consistent standards for exchanging data and models (EVO 2013<ref name="EVO"></ref>). The project activities include developing cyber infrastructure, cloud-enabled environmental models, and a number of exemplar web-based services concerning soil and water management at both local and national scales (EVO 2013<ref name="EVO"></ref>). Exemplars developed within the course of the two year pilot project focus on a range of environmental problems, which directly affect the well-being of people in the UK, e.g.: studying national-scale nutrient fate using linked hydrogeological and biochemical models, developing a system to assess the effects of different land management practices on reducing diffuse pollution from agriculture, advancing modelling capabilities for drought and flood predictions to address and mitigate the effects of climate change, or establishing technologies for studying biodiversity and ecosystem service sustainability (EVO 2013<ref name="EVO"></ref>). EVO aims to provide different groups of users, from scientists to local stakeholders, with free and easy access to expert knowledge by combining assets from various sources with novel tools for data analysis and visualisation (Gurney et al., 2011<ref name="Gurney">GURNEY, R, EMMETT, B, MCDONALD, A, BLAIR, G, BUYTAERT, W, FREER, J E, HAYGARTH, P, REES, G, TETZLAFF, D and EVO SCIENCE TEAM. The Environmental Virtual Observatory: A New Vision for Catchment Science. American Geophysical Union Fall Meeting 2011. </ref>). The system is designed to promote feedback, ownership, community involvement, and better communication between technical ad non-technical users (EVO 2013<ref name="EVO"></ref>). An example of a community tool established within EVO is The Local Landscape Visualisation Tool, developed by engaging stakeholders in three catchments in the UK: the Afon Dyfi, the River Tarland, and the River Eden (Wilkinson et al., 2013<ref name="Wilkinson">WILKINSON, M, BEVEN, K, BREWER, P, EL-KHATIB, Y, GEMMELL, A, HAYGARTH, P, MACKAY, E, MACKLIN, M, MARSHALL, K, QUINN, P, STUTTER, M., THOMAS, N & VITOLO, C. The Environmental Virtual Observatory (EVO) local exemplar: A cloud based local landscape learning visualisation tool for communicating flood risk to catchment stakeholders. EGU General Assembly 2013 Vienna Austria. </ref>). The tool is accessed via a web portal and communicates flood risk in the local impacted communities. It is based on a number of services, i.e.: catchment datasets, hydrological models, and visualisation tools. Users can access real time data concerning river levels, rainfall, weather, and water quality, which is additionally supported by webcam images, or can use cloud-based models to explore how different land management strategies might affect the risk of flooding (Wilkinson et al., 2013<ref name="Wilkinson"></ref>).

	Last but not least, web services can be used to link different modelling frameworks. Hydrologic studies traditionally did not consider bi-directional interactions between atmosphere and water bodies. However, as the scale of the models increase, the assumption about the lack of feedback between the land surface and the atmosphere may no longer hold and bi-directional coupling becomes important (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Up to date coupling of hydrological and climate models has been hindered by discrepancies between both technologies, namely climate models run on high performance computers while hydrologic models run on personal computers (Goodall et al., 2013<ref name="Goodall 2013"></ref>, Saint and Murphy 2010<ref name="Saint"></ref>). Additionally, there is a lack of established techniques for transferring data between differing spatial scales of climate and hydrologic models (Goodall et al., 2013<ref name="Goodall 2011"></ref>). Hydrological Modelling for Assessing Climate Change Impacts at different Scales project (HYACINTS) coupled climate model HIRHAM and physically distributed hydrological model MIKE SHE for the whole of Denmark by migrating both models into the OpenMI standard (HYACINTS 2013<ref name="Hyacints">HYACINTS 2013. ''Hydrological Modelling for Assessing Climate Change Impacts at different Scales Project Website ''[Online]. Last revised 26 June 2009. [cited 14 November 2013]. Available: [http://hyacints.dk/main_uk/main.html http://hyacints.dk/main_uk/main.html.]</ref>). Method based on statistical downscaling and bias-correction was developed to enable data transfer across different grids (HYACINTS 2013<ref name="Hyacints"></ref>). While the project achieved integration of models from different domains, this required migrating them to the same standard. Goodall et al., (2013)<ref name="Goodall 2013"></ref> proposed a novel approach to loosely couple climate and hydrologic models using web services, which enabled integration of different modelling frameworks. The researchers did not address the problem of data scalability between climate and hydrologic models but merely aimed to develop technically feasible strategy for coupling such models. In the proposed approach web services are used to pass data between a hydrologic model running on desktop computer and a climate/weather model running in HPC environment (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The prototype developed in the study was a two-way coupled system composed of the Community Atmosphere Model (CAM) and the Soil and Water Assessment Tool (SWAT) (Goodall et al., 2013<ref name="Goodall 2013"></ref>). CAM implemented with ESMF was made available as a web service. SWAT was provided as an OpenMI compliant model and CAM model was wrapped with an OpenMI interface (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The execution was controlled and implemented by OpenMI’s Configuration Editor (Saint and Murphy 2010<ref name="Saint"></ref>). This study proved that coupling of two disparate modelling systems is feasible while still maintaining the models' original structure and purpose (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The study provided a technical solution for coupling models running on different computing platforms, e.g.: PC and HPC, different HPCs, or cloud (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Bridging the gap between OpenMI and ESMF was possible due to features that both standards provide, namely: ESMF supporting web services and OpenMI supporting a wrapper for accessing external services (Goodall et al., 2013). Both frameworks are widely used within their respective communities and their integration is an important milestone in modelling coupled hydrology-climate systems (Saint and Murphy 2010<ref name="Saint"></ref>).		Last but not least, web services can be used to link different modelling frameworks. Hydrologic studies traditionally did not consider bi-directional interactions between atmosphere and water bodies. However, as the scale of the models increase, the assumption about the lack of feedback between the land surface and the atmosphere may no longer hold and bi-directional coupling becomes important (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Up to date coupling of hydrological and climate models has been hindered by discrepancies between both technologies, namely climate models run on high performance computers while hydrologic models run on personal computers (Goodall et al., 2013<ref name="Goodall 2013"></ref>, Saint and Murphy 2010<ref name="Saint"></ref>). Additionally, there is a lack of established techniques for transferring data between differing spatial scales of climate and hydrologic models (Goodall et al., 2013<ref name="Goodall 2011"></ref>). Hydrological Modelling for Assessing Climate Change Impacts at different Scales project (HYACINTS) coupled climate model HIRHAM and physically distributed hydrological model MIKE SHE for the whole of Denmark by migrating both models into the OpenMI standard (HYACINTS 2013<ref name="Hyacints">HYACINTS 2013. ''Hydrological Modelling for Assessing Climate Change Impacts at different Scales Project Website ''[Online]. Last revised 26 June 2009. [cited 14 November 2013]. Available: [http://hyacints.dk/main_uk/main.html http://hyacints.dk/main_uk/main.html.]</ref>). Method based on statistical downscaling and bias-correction was developed to enable data transfer across different grids (HYACINTS 2013<ref name="Hyacints"></ref>). While the project achieved integration of models from different domains, this required migrating them to the same standard. Goodall et al., (2013)<ref name="Goodall 2013"></ref> proposed a novel approach to loosely couple climate and hydrologic models using web services, which enabled integration of different modelling frameworks. The researchers did not address the problem of data scalability between climate and hydrologic models but merely aimed to develop technically feasible strategy for coupling such models. In the proposed approach web services are used to pass data between a hydrologic model running on desktop computer and a climate/weather model running in HPC environment (Goodall et al., 2013<ref name="Goodall 2013">GOODALL, J L, SAINT, K D, ERCAN, M B, BRILEY, L J, MURPHY, S, YOU, H, DELUCA, C, and ROOD, R B. 2013. Coupling climate and hydrological models: Interoperability through Web Services. ''Environmental Modelling and Software'', 46 250–259.</ref>). The prototype developed in the study was a two-way coupled system composed of the Community Atmosphere Model (CAM) and the Soil and Water Assessment Tool (SWAT) (Goodall et al., 2013<ref name="Goodall 2013"></ref>). CAM implemented with ESMF was made available as a web service. SWAT was provided as an OpenMI compliant model and CAM model was wrapped with an OpenMI interface (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The execution was controlled and implemented by OpenMI’s Configuration Editor (Saint and Murphy 2010<ref name="Saint"></ref>). This study proved that coupling of two disparate modelling systems is feasible while still maintaining the models' original structure and purpose (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The study provided a technical solution for coupling models running on different computing platforms, e.g.: PC and HPC, different HPCs, or cloud (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Bridging the gap between OpenMI and ESMF was possible due to features that both standards provide, namely: ESMF supporting web services and OpenMI supporting a wrapper for accessing external services (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Both frameworks are widely used within their respective communities and their integration is an important milestone in modelling coupled hydrology-climate systems (Saint and Murphy 2010<ref name="Saint"></ref>).

	==References==		==References==

	[[category:OR/14/022 Couplers for linking environmental models: Scoping study and potential next steps \| 04]]		[[category:OR/14/022 Couplers for linking environmental models: Scoping study and potential next steps \| 04]]

Ajhil: /* Web services */

2022-07-01T09:41:46Z

Web services

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	Applications operating as web services are based on components that are independent, distributed, loosely-coupled and exchange data over a computer network. In the hydrological domain web services are used in a number of ways, e.g.: to integrate hydrologic data from heterogeneous sources; to link modelling frameworks with databases; to connect models, databases, and analysis tools into water resources decision support systems; or to join modelling systems from different domains (e.g.: hydrology and climate).		Applications operating as web services are based on components that are independent, distributed, loosely-coupled and exchange data over a computer network. In the hydrological domain web services are used in a number of ways, e.g.: to integrate hydrologic data from heterogeneous sources; to link modelling frameworks with databases; to connect models, databases, and analysis tools into water resources decision support systems; or to join modelling systems from different domains (e.g.: hydrology and climate).

	There are a number of examples of successful use of service-oriented technology for environmental data integration. One such example is Hydrologic Information System (HIS), created by the Consortium of Universities for the Advancement of Hydrological Science Inc. (CUAHSI) — an organisation of more than 100 US universities aimed at developing infrastructure and services for the advancement of the hydrologic sciences (Peckham and Goodall 2013). HIS is composed of hydrologic databases and servers connected through web services (Peckham and Goodall 2013<ref name="Peckham and Goodall">PECKHAM, S D and GOODALL, J L. 2013. Driving plug-and-play models with data from web services: A demonstration of interoperability between CSDMS and CUAHSI-HIS. ''Computers and Geosciences, ''53, 154–161. </ref>). It employs WaterOneFlow web service interface and Water Markup Language (WaterML) for data transmission to enable integration of hydrologic data from heterogeneous data sources into one ‘virtual database’ (Goodall et al., 2011<ref name="Goodall 2011"></ref>).		There are a number of examples of successful use of service-oriented technology for environmental data integration. One such example is Hydrologic Information System (HIS), created by the Consortium of Universities for the Advancement of Hydrological Science Inc. (CUAHSI) — an organisation of more than 100 US universities aimed at developing infrastructure and services for the advancement of the hydrologic sciences (Peckham and Goodall 2013<ref name="Peckham 2013">PECKHAM, S D, and GOODALL, J L. 2013. Driving plug-and-play models with data from web services: A demonstration of interoperability between CSDMS and CUAHSI-HIS. ''Computers and Geosciences'', 53, 154–161.</ref>). HIS is composed of hydrologic databases and servers connected through web services (Peckham and Goodall 2013<ref name="Peckham and Goodall">PECKHAM, S D and GOODALL, J L. 2013. Driving plug-and-play models with data from web services: A demonstration of interoperability between CSDMS and CUAHSI-HIS. ''Computers and Geosciences, ''53, 154–161. </ref>). It employs WaterOneFlow web service interface and Water Markup Language (WaterML) for data transmission to enable integration of hydrologic data from heterogeneous data sources into one ‘virtual database’ (Goodall et al., 2011<ref name="Goodall 2011"></ref>).

	Research efforts focus also on ways to integrate data and modelling systems. HydroDesktop is open source GIS-enabled software developed by CUASHIU HIS, which allows accessing HIS services from a personal computer. It not only provides capabilities for data querying, downloading, visualisation, editing, graphing, analysis, and exporting to different formats but also supports integrated model development and use of the retrieved data in simulations (HydroDesktop 2013<ref name="Hydrodesktop">HYDRODESKTOP 2013. ''HydroDesktop CUAHSI Open Source Hydrologic Data Tools Website ''[Online]. Last revised 13 March 2012. [cited 14 November 2013]. Available: [http://his.cuahsi.org/hdhelp/welcome.html http://his.cuahsi.org/hdhelp/welcome.html.]</ref>). HydroModeler is a HydroDesktop plug-in, based on OpenMI Configuration Editor, which provides functionality for building and executing model compositions from within HydroDesktop (HydroDesktop 2013<ref name="Hydrodesktop"></ref>). Another example of data and modelling systems integration stems from the partnership between CSDMS and HIS. As a result of this cooperation a novel system was developed, which allows accessing HIS data through web services calls from within the CSDMS modelling environment (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>). This functionality was achieved by incorporating an additional component, called DataHIS, within a CSDMS model composition. It is planned that CSDMS web services are further developed, provided that other environmental databases employ standardised interfaces for data retrieval and integration. It is envisioned that in the future CSDMS components could become web services themselves, potentially available to client applications such as HydroDesktop and HydroModeler (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>).		Research efforts focus also on ways to integrate data and modelling systems. HydroDesktop is open source GIS-enabled software developed by CUASHIU HIS, which allows accessing HIS services from a personal computer. It not only provides capabilities for data querying, downloading, visualisation, editing, graphing, analysis, and exporting to different formats but also supports integrated model development and use of the retrieved data in simulations (HydroDesktop 2013<ref name="Hydrodesktop">HYDRODESKTOP 2013. ''HydroDesktop CUAHSI Open Source Hydrologic Data Tools Website ''[Online]. Last revised 13 March 2012. [cited 14 November 2013]. Available: [http://his.cuahsi.org/hdhelp/welcome.html http://his.cuahsi.org/hdhelp/welcome.html.]</ref>). HydroModeler is a HydroDesktop plug-in, based on OpenMI Configuration Editor, which provides functionality for building and executing model compositions from within HydroDesktop (HydroDesktop 2013<ref name="Hydrodesktop"></ref>). Another example of data and modelling systems integration stems from the partnership between CSDMS and HIS. As a result of this cooperation a novel system was developed, which allows accessing HIS data through web services calls from within the CSDMS modelling environment (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>). This functionality was achieved by incorporating an additional component, called DataHIS, within a CSDMS model composition. It is planned that CSDMS web services are further developed, provided that other environmental databases employ standardised interfaces for data retrieval and integration. It is envisioned that in the future CSDMS components could become web services themselves, potentially available to client applications such as HydroDesktop and HydroModeler (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>).

Ajhil: /* CESM -CPL 7 (Framework and Coupler) */

2022-07-01T09:39:12Z

CESM -CPL 7 (Framework and Coupler)

← Older revision		Revision as of 10:39, 1 July 2022
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	[[Image:OR14022 fig1.jpg\|thumb\|center\|500px\| '''Figure 1'''    A typical dynamic interaction between an ensemble component using the IRF method.]]		[[Image:OR14022 fig1.jpg\|thumb\|center\|500px\| '''Figure 1'''    A typical dynamic interaction between an ensemble component using the IRF method.]]
	===CESM -CPL 7 (Framework and Coupler)===		===CESM-CPL 7 (Framework and Coupler)===
	====Overview====		====Overview====
	The Community Earth System Model (CESM) framework is used by researchers at the University Corporation for Atmospheric Research (UCAR) and the National Center for Atmospheric Research (NCAR) to couple land, sea, ice and atmospheric models using the CESM coupler CPL7 (Figure 2). The CESM replaces the previous Community Climate System Model (CCSM) modelling framework. CPL7 is designed to synchronise component time-stepping within the framework, manage component data communication, conservatively map data between component grids, and compute fluxes between components. While the processor configuration is relatively flexible and components can be run sequentially or concurrently, the sequencing of components in the driver (main CESM program) is fixed and independent of the processor layout. CESM components are called via the standard IRF method. The framework description used in this report is modified from Craig (2011)<ref name="Craig">CRAIG, T, 2011. CPL7 User’s Guide. [http://www.cesm.ucar.edu/models/cesm1.0/cpl7/cpl7_doc/ug.pdf http://www.cesm.ucar.edu/models/cesm1.0/cpl7/cpl7_doc/ug.pdf] (accessed 14.02.14). </ref>.		The Community Earth System Model (CESM) framework is used by researchers at the University Corporation for Atmospheric Research (UCAR) and the National Center for Atmospheric Research (NCAR) to couple land, sea, ice and atmospheric models using the CESM coupler CPL7 (Figure 2). The CESM replaces the previous Community Climate System Model (CCSM) modelling framework. CPL7 is designed to synchronise component time-stepping within the framework, manage component data communication, conservatively map data between component grids, and compute fluxes between components. While the processor configuration is relatively flexible and components can be run sequentially or concurrently, the sequencing of components in the driver (main CESM program) is fixed and independent of the processor layout. CESM components are called via the standard IRF method. The framework description used in this report is modified from Craig (2011)<ref name="Craig">CRAIG, T, 2011. CPL7 User’s Guide. [http://www.cesm.ucar.edu/models/cesm1.0/cpl7/cpl7_doc/ug.pdf http://www.cesm.ucar.edu/models/cesm1.0/cpl7/cpl7_doc/ug.pdf] (accessed 14.02.14). </ref>.

Ajhil at 09:38, 1 July 2022

2022-07-01T09:38:57Z

Show changes

Ajhil at 09:34, 1 July 2022

2022-07-01T09:34:00Z

← Older revision		Revision as of 10:34, 1 July 2022
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	==References==		==References==

	[[category:OR/14/022 Couplers for linking environmental models: Scoping study and potential next steps \| 03]]		[[category:OR/14/022 Couplers for linking environmental models: Scoping study and potential next steps \| 04]]

Ajhil at 11:38, 29 November 2019

2019-11-29T11:38:36Z

← Older revision		Revision as of 12:38, 29 November 2019
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	====Kepler====		====Kepler====
	Kepler is an open-source desktop application for creating scientific workflows, which emerged from Ptolemy II (Kepler 2013<ref name="Kepler 2013">KEPLER 2013. ''The Kepler project ''[Online]. [cited 14 November 2013]. Available: [https://kepler-/ https://kepler-] project.org/. </ref>). Ptolemy II is a framework allowing for a number of different modes of execution, which was developed at the University of California at Berkley and originally targeted at bioinformatics, computational chemistry, ecoinformatics, and geoinformatics (Kepler 2013a<ref name="Kepler 2013a">KEPLER. 2013a. Getting started with Kepler Manual [Online]. [cited 14 November 2013]. Available: [https://kepler-project.org/ https://kepler-project.org/]. </ref>, Kepler 2013b<ref name="Kepler 2013b">KEPLER. 2013b. Kepler User Manual [Online]. [cited 14 November 2013]. Available: [https://kepler-project.org/ https://kepler-project.org/]. </ref>). Ptolemy II and Kepler are characterised by separation of workflow components from the workflow orchestration, which enables direct reusability of components (Kepler 2013b<ref name="Kepler 2013b"></ref>). Workflows can be executed either from the GUI or from a command line (Kepler 2013<ref name="Kepler 2013"></ref>). Each component is represented graphically in the GUI by an icon reflecting its function (Kepler 2013a<ref name="Kepler 2013a"></ref>). Kepler is featuring a library of above 530 ready components (Kepler 2013b<ref name="Kepler 2013b"></ref>), which facilitate a number of tasks, among others: remote data access, processing, analysis and visualization; transformations for syntactically incompatible components; GIS processing; execution of command line applications; statistical analysis using R or Matlab; web services invocation; cluster and grid computing, execution and monitoring (Goodall et al., 2011<ref name="Goodall 2011">~~GOODALL, J L., ROBINSON, B F and CASTRONOVA, A M. 2011. Modeling water resource systems using a service-oriented computing paradigm. ''Environmental Modelling and Software 2''6''', '''573–582.~~ </ref>, Kepler 2013b<ref name="Kepler 2013b"></ref>, Kepler 2013<ref name="Kepler 2013"></ref>). Kepler is maintained for Windows, OSX, and Linux operating systems (Kepler 2013<ref name="Kepler 2013"></ref>).		Kepler is an open-source desktop application for creating scientific workflows, which emerged from Ptolemy II (Kepler 2013<ref name="Kepler 2013">KEPLER 2013. ''The Kepler project ''[Online]. [cited 14 November 2013]. Available: [https://kepler-/ https://kepler-] project.org/. </ref>). Ptolemy II is a framework allowing for a number of different modes of execution, which was developed at the University of California at Berkley and originally targeted at bioinformatics, computational chemistry, ecoinformatics, and geoinformatics (Kepler 2013a<ref name="Kepler 2013a">KEPLER. 2013a. Getting started with Kepler Manual [Online]. [cited 14 November 2013]. Available: [https://kepler-project.org/ https://kepler-project.org/]. </ref>, Kepler 2013b<ref name="Kepler 2013b">KEPLER. 2013b. Kepler User Manual [Online]. [cited 14 November 2013]. Available: [https://kepler-project.org/ https://kepler-project.org/]. </ref>). Ptolemy II and Kepler are characterised by separation of workflow components from the workflow orchestration, which enables direct reusability of components (Kepler 2013b<ref name="Kepler 2013b"></ref>). Workflows can be executed either from the GUI or from a command line (Kepler 2013<ref name="Kepler 2013"></ref>). Each component is represented graphically in the GUI by an icon reflecting its function (Kepler 2013a<ref name="Kepler 2013a"></ref>). Kepler is featuring a library of above 530 ready components (Kepler 2013b<ref name="Kepler 2013b"></ref>), which facilitate a number of tasks, among others: remote data access, processing, analysis and visualization; transformations for syntactically incompatible components; GIS processing; execution of command line applications; statistical analysis using R or Matlab; web services invocation; cluster and grid computing, execution and monitoring (Goodall et al., 2011<ref name="Goodall 2011"></ref>, Kepler 2013b<ref name="Kepler 2013b"></ref>, Kepler 2013<ref name="Kepler 2013"></ref>). Kepler is maintained for Windows, OSX, and Linux operating systems (Kepler 2013<ref name="Kepler 2013"></ref>).

	Kepler workflow is composed of components, called actors, each performing a different function. A director is a special type of an actor that controls (directs) the execution of a workflow. Workflows can have a number of sub-workflows (also called composite actors), each comprised of a collection of actors performing complex embedded task and each controlled by its own director (Kepler 2013a<ref name="Kepler 2013a"></ref>). Kepler is developed in Java, however, components written in other language can be adopted by using wrappers (Kepler 2013b<ref name="Kepler 2013b"></ref>).		Kepler workflow is composed of components, called actors, each performing a different function. A director is a special type of an actor that controls (directs) the execution of a workflow. Workflows can have a number of sub-workflows (also called composite actors), each comprised of a collection of actors performing complex embedded task and each controlled by its own director (Kepler 2013a<ref name="Kepler 2013a"></ref>). Kepler is developed in Java, however, components written in other language can be adopted by using wrappers (Kepler 2013b<ref name="Kepler 2013b"></ref>).
Line 210:		Line 210:
	Applications operating as web services are based on components that are independent, distributed, loosely-coupled and exchange data over a computer network. In the hydrological domain web services are used in a number of ways, e.g.: to integrate hydrologic data from heterogeneous sources; to link modelling frameworks with databases; to connect models, databases, and analysis tools into water resources decision support systems; or to join modelling systems from different domains (e.g.: hydrology and climate).		Applications operating as web services are based on components that are independent, distributed, loosely-coupled and exchange data over a computer network. In the hydrological domain web services are used in a number of ways, e.g.: to integrate hydrologic data from heterogeneous sources; to link modelling frameworks with databases; to connect models, databases, and analysis tools into water resources decision support systems; or to join modelling systems from different domains (e.g.: hydrology and climate).

	There are a number of examples of successful use of service-oriented technology for environmental data integration. One such example is Hydrologic Information System (HIS), created by the Consortium of Universities for the Advancement of Hydrological Science Inc. (CUAHSI) — an organisation of more than 100 US universities aimed at developing infrastructure and services for the advancement of the hydrologic sciences (Peckham and Goodall 2013). HIS is composed of hydrologic databases and servers connected through web services (Peckham and Goodall 2013<ref name="Peckham and Goodall">PECKHAM, S D and GOODALL, J L. 2013. Driving plug-and-play models with data from web services: A demonstration of interoperability between CSDMS and CUAHSI-HIS. ''Computers and Geosciences, ''53, 154–161. </ref>). It employs WaterOneFlow web service interface and Water Markup Language (WaterML) for data transmission to enable integration of hydrologic data from heterogeneous data sources into one ‘virtual database’ (Goodall et al., 2011<ref name="Goodall 2011">~~GOODALL, J L., ROBINSON, B F and CASTRONOVA, A M. 2011. Modeling water resource systems using a service-oriented computing paradigm. ''Environmental Modelling and Software 2''6''', '''573–582.~~ </ref>).		There are a number of examples of successful use of service-oriented technology for environmental data integration. One such example is Hydrologic Information System (HIS), created by the Consortium of Universities for the Advancement of Hydrological Science Inc. (CUAHSI) — an organisation of more than 100 US universities aimed at developing infrastructure and services for the advancement of the hydrologic sciences (Peckham and Goodall 2013). HIS is composed of hydrologic databases and servers connected through web services (Peckham and Goodall 2013<ref name="Peckham and Goodall">PECKHAM, S D and GOODALL, J L. 2013. Driving plug-and-play models with data from web services: A demonstration of interoperability between CSDMS and CUAHSI-HIS. ''Computers and Geosciences, ''53, 154–161. </ref>). It employs WaterOneFlow web service interface and Water Markup Language (WaterML) for data transmission to enable integration of hydrologic data from heterogeneous data sources into one ‘virtual database’ (Goodall et al., 2011<ref name="Goodall 2011"></ref>).

	Research efforts focus also on ways to integrate data and modelling systems. HydroDesktop is open source GIS-enabled software developed by CUASHIU HIS, which allows accessing HIS services from a personal computer. It not only provides capabilities for data querying, downloading, visualisation, editing, graphing, analysis, and exporting to different formats but also supports integrated model development and use of the retrieved data in simulations (HydroDesktop 2013<ref name="Hydrodesktop">HYDRODESKTOP 2013. ''HydroDesktop CUAHSI Open Source Hydrologic Data Tools Website ''[Online]. Last revised 13 March 2012. [cited 14 November 2013]. Available: [http://his.cuahsi.org/hdhelp/welcome.html http://his.cuahsi.org/hdhelp/welcome.html.]</ref>). HydroModeler is a HydroDesktop plug-in, based on OpenMI Configuration Editor, which provides functionality for building and executing model compositions from within HydroDesktop (HydroDesktop 2013<ref name="Hydrodesktop"></ref>). Another example of data and modelling systems integration stems from the partnership between CSDMS and HIS. As a result of this cooperation a novel system was developed, which allows accessing HIS data through web services calls from within the CSDMS modelling environment (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>). This functionality was achieved by incorporating an additional component, called DataHIS, within a CSDMS model composition. It is planned that CSDMS web services are further developed, provided that other environmental databases employ standardised interfaces for data retrieval and integration. It is envisioned that in the future CSDMS components could become web services themselves, potentially available to client applications such as HydroDesktop and HydroModeler (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>).		Research efforts focus also on ways to integrate data and modelling systems. HydroDesktop is open source GIS-enabled software developed by CUASHIU HIS, which allows accessing HIS services from a personal computer. It not only provides capabilities for data querying, downloading, visualisation, editing, graphing, analysis, and exporting to different formats but also supports integrated model development and use of the retrieved data in simulations (HydroDesktop 2013<ref name="Hydrodesktop">HYDRODESKTOP 2013. ''HydroDesktop CUAHSI Open Source Hydrologic Data Tools Website ''[Online]. Last revised 13 March 2012. [cited 14 November 2013]. Available: [http://his.cuahsi.org/hdhelp/welcome.html http://his.cuahsi.org/hdhelp/welcome.html.]</ref>). HydroModeler is a HydroDesktop plug-in, based on OpenMI Configuration Editor, which provides functionality for building and executing model compositions from within HydroDesktop (HydroDesktop 2013<ref name="Hydrodesktop"></ref>). Another example of data and modelling systems integration stems from the partnership between CSDMS and HIS. As a result of this cooperation a novel system was developed, which allows accessing HIS data through web services calls from within the CSDMS modelling environment (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>). This functionality was achieved by incorporating an additional component, called DataHIS, within a CSDMS model composition. It is planned that CSDMS web services are further developed, provided that other environmental databases employ standardised interfaces for data retrieval and integration. It is envisioned that in the future CSDMS components could become web services themselves, potentially available to client applications such as HydroDesktop and HydroModeler (Peckham and Goodall 2013<ref name="Peckham and Goodall"></ref>).

Dbk at 13:43, 7 August 2015

2015-08-07T13:43:37Z

← Older revision		Revision as of 14:43, 7 August 2015
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	Open Modelling Interface (OpenMI) Standard was established by a consortium of 14 organisations from seven countries, in the course of the HarmonIT project co-funded through the European Commison’s Fifth Framework programme (Moore et al., 2010<ref name="Moore 2010">MOORE, R, GIJSBERS, P, FORTUNE, D, GREGERSEN, J, BLIND, M, GROOSS, J and VANECEK, S. 2010. OpenMI Document Series: Scope for the OpenMI (Version 2.0). ''In: ''MOORE, R. (ed.). </ref>). It was originally developed to address the Water Framework Directive's call for integrated water resources at the catchment level (Moore and Tindall 2005<ref name="Moore 2005">MOORE, R V and TINDALL, C I. 2005. An overview of the open modelling interface and environment (the OpenMI). ''Environmental Science & Policy, ''8 279–286. </ref>), however, its application was later extended to other domains of environmental management (OATC 2010a<ref name="OATC 2010a">OATC 2010a. OpenMI Document Series: The OpenMI 'in a Nutshell' for the OpenMI (Version 2.0). The OpenMI Association Technical Committee. ''In: ''MOORE, R. (ed.). </ref>). OpenMI is maintained and promoted by the OpenMI Association (OpenMI 2013<ref name="Openmi">OPENMI 2013. ''The OpenMI Association Website ''[Online]. [cited 14 November 2013]. Available: [http://www.openmi.org/ http://www.openmi.org/.]</ref>), and is supported by the FluidEarth initiative of HR Wallingford (FluidEarth 2013<ref name="Fluidearth">FLUIDEARTH 2013. ''FluidEarth HR Wallingford Website ''[Online]. [cited 14 November 2013]. Available: [http://fluidearth.net/default.aspx http://fluidearth.net/default.aspx.]</ref>), which provides tools for robust model integration, e.g.: FluidEarth2 Toolkit. OpenMI is equipped with GUI (OpenMI Configuration Editor), which facilitates creating and running compositions (Goodall et al., 2011<ref name="Goodall 2011">GOODALL, J L., ROBINSON, B F. and CASTRONOVA, A M. 2011. Modeling water resource systems using a service-oriented computing paradigm. ''Environmental Modelling and Software 2''6''', '''573–582. </ref>).		Open Modelling Interface (OpenMI) Standard was established by a consortium of 14 organisations from seven countries, in the course of the HarmonIT project co-funded through the European Commison’s Fifth Framework programme (Moore et al., 2010<ref name="Moore 2010">MOORE, R, GIJSBERS, P, FORTUNE, D, GREGERSEN, J, BLIND, M, GROOSS, J and VANECEK, S. 2010. OpenMI Document Series: Scope for the OpenMI (Version 2.0). ''In: ''MOORE, R. (ed.). </ref>). It was originally developed to address the Water Framework Directive's call for integrated water resources at the catchment level (Moore and Tindall 2005<ref name="Moore 2005">MOORE, R V and TINDALL, C I. 2005. An overview of the open modelling interface and environment (the OpenMI). ''Environmental Science & Policy, ''8 279–286. </ref>), however, its application was later extended to other domains of environmental management (OATC 2010a<ref name="OATC 2010a">OATC 2010a. OpenMI Document Series: The OpenMI 'in a Nutshell' for the OpenMI (Version 2.0). The OpenMI Association Technical Committee. ''In: ''MOORE, R. (ed.). </ref>). OpenMI is maintained and promoted by the OpenMI Association (OpenMI 2013<ref name="Openmi">OPENMI 2013. ''The OpenMI Association Website ''[Online]. [cited 14 November 2013]. Available: [http://www.openmi.org/ http://www.openmi.org/.]</ref>), and is supported by the FluidEarth initiative of HR Wallingford (FluidEarth 2013<ref name="Fluidearth">FLUIDEARTH 2013. ''FluidEarth HR Wallingford Website ''[Online]. [cited 14 November 2013]. Available: [http://fluidearth.net/default.aspx http://fluidearth.net/default.aspx.]</ref>), which provides tools for robust model integration, e.g.: FluidEarth2 Toolkit. OpenMI is equipped with GUI (OpenMI Configuration Editor), which facilitates creating and running compositions (Goodall et al., 2011<ref name="Goodall 2011">GOODALL, J L., ROBINSON, B F. and CASTRONOVA, A M. 2011. Modeling water resource systems using a service-oriented computing paradigm. ''Environmental Modelling and Software 2''6''', '''573–582. </ref>).

	Components in OpenMI are called 'Linkable Components' (Lu 2011<ref name="Lu">LU, B. 2011. ''Development of A Hydrologic Community Modeling System Using A Workflow Engine. ''PhD thesis, Drexel University. </ref>) and their architectural design follow initialise/run/finalise cycle (Lawrence et al., Manuscript<ref name="Lawrence"></ref>). They must be accompanied by metadata provided in the form of XML files (OATC 2010a<ref name="OATC 2010a"></ref>) and encoded using either VB.Net or C# (Lu 2011<ref name="Lu"></ref>). Models written in other languages (e.g.: Fortran, C, C++, F#, Matlab, etc.) can be integrated in OpenMI after implementing appropriate wrappers (OATC 2010a<ref name="OATC 2010a"></ref>). A number of tools are available to assist users in developing their applications, including wrappers, which are provided in the form of code libraries (Software Development Kits or SDKs) (OATC 2010a<ref name="OATC 2010a"></ref>). A set of interfaces need to be implemented to make a component OpenMI-compliant (OATC 2010a<ref name="OATC 2010a"></ref>), with the central one being 'ILinkableComponent' (OATC 2010b<ref name="OATC 2010b">OATC 2010b. OpenMI Document Series: OpenMI Standard 2 Specification for the OpenMI (Version 2.0). The OpenMI Association Technical Committee. In: MOORE, R. (ed.). </ref>).		Components in OpenMI are called 'Linkable Components' (Lu 2011<ref name="Lu">LU, B. 2011. ''Development of A Hydrologic Community Modeling System Using A Workflow Engine. ''PhD thesis, Drexel University. </ref>) and their architectural design follow initialise/run/finalise cycle (Lawrence et al., Manuscript<ref name="Lawrence">LAWRENCE, B N, BALAJI, V, CARTER, M, DELUCA, C, EASTERBROOK, S, FORD, R., HUGHES, A & HARDING, R. Manuscript. Bridging Communities: Technical Concerns for Integrating Environmental Models. </ref>). They must be accompanied by metadata provided in the form of XML files (OATC 2010a<ref name="OATC 2010a"></ref>) and encoded using either VB.Net or C# (Lu 2011<ref name="Lu"></ref>). Models written in other languages (e.g.: Fortran, C, C++, F#, Matlab, etc.) can be integrated in OpenMI after implementing appropriate wrappers (OATC 2010a<ref name="OATC 2010a"></ref>). A number of tools are available to assist users in developing their applications, including wrappers, which are provided in the form of code libraries (Software Development Kits or SDKs) (OATC 2010a<ref name="OATC 2010a"></ref>). A set of interfaces need to be implemented to make a component OpenMI-compliant (OATC 2010a<ref name="OATC 2010a"></ref>), with the central one being 'ILinkableComponent' (OATC 2010b<ref name="OATC 2010b">OATC 2010b. OpenMI Document Series: OpenMI Standard 2 Specification for the OpenMI (Version 2.0). The OpenMI Association Technical Committee. In: MOORE, R. (ed.). </ref>).

	The primary data structure is the 'ExchangeItem', which can be of two different types: 'InputExchangeItem' and 'OutputExchangeItem' (Saint and Murphy 2010<ref name="Saint">SAINT, K & MURPHY, S. End-to-End Workflows for Coupled Climate and Hydrological Modeling. International Congress on Environmental Modelling and Software, Modelling for Environment's Sake, Fifth Biennial Meeting 2010 Ottawa, Canada.</ref>). The ExchangeItems can be either 'Quantities' or 'Elementsets' (Lu 2011<ref name="Lu"></ref>). A Quantity contains metadata of a variable, while an Elementset provides its spatial information (Lu 2011<ref name="Lu"></ref>). To enable linking of data expressed in different units, each Quantity is provided with a conversion formula to standard SI system units (OATC 2010b<ref name="OATC 2010b"></ref>). Elementsets contain references to the coordinate system used, which allows mapping between different systems (OATC 2010b<ref name="OATC 2010b"></ref>).		The primary data structure is the 'ExchangeItem', which can be of two different types: 'InputExchangeItem' and 'OutputExchangeItem' (Saint and Murphy 2010<ref name="Saint">SAINT, K & MURPHY, S. End-to-End Workflows for Coupled Climate and Hydrological Modeling. International Congress on Environmental Modelling and Software, Modelling for Environment's Sake, Fifth Biennial Meeting 2010 Ottawa, Canada.</ref>). The ExchangeItems can be either 'Quantities' or 'Elementsets' (Lu 2011<ref name="Lu"></ref>). A Quantity contains metadata of a variable, while an Elementset provides its spatial information (Lu 2011<ref name="Lu"></ref>). To enable linking of data expressed in different units, each Quantity is provided with a conversion formula to standard SI system units (OATC 2010b<ref name="OATC 2010b"></ref>). Elementsets contain references to the coordinate system used, which allows mapping between different systems (OATC 2010b<ref name="OATC 2010b"></ref>).
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	Another technology that could potentially be harnessed for building decision support systems is cloud computing. Environmental Virtual Observatory (EVO) pilot project, sponsored by the UK’s Natural Environment Research Council (NERC), employs cloud computing to integrate datasets, models and tools for cost-effective, efficient and transparent environmental monitoring and decision making (EVO 2013<ref name="EVO">EVO 2013. ''Environmental Virtual Observatory Website ''[Online]. [cited 14 November 2013]. Available: [http://www.evo-uk.org/ http://www.evo-uk.org/.]</ref>). EVO works with other international partners (e.g.: CUAHSI, NeON) to develop consistent standards for exchanging data and models (EVO 2013<ref name="EVO"></ref>). The project activities include developing cyber infrastructure, cloud-enabled environmental models, and a number of exemplar web-based services concerning soil and water management at both local and national scales (EVO 2013<ref name="EVO"></ref>). Exemplars developed within the course of the two year pilot project focus on a range of environmental problems, which directly affect the well-being of people in the UK, e.g.: studying national-scale nutrient fate using linked hydrogeological and biochemical models, developing a system to assess the effects of different land management practices on reducing diffuse pollution from agriculture, advancing modelling capabilities for drought and flood predictions to address and mitigate the effects of climate change, or establishing technologies for studying biodiversity and ecosystem service sustainability (EVO 2013<ref name="EVO"></ref>). EVO aims to provide different groups of users, from scientists to local stakeholders, with free and easy access to expert knowledge by combining assets from various sources with novel tools for data analysis and visualisation (Gurney et al., 2011<ref name="Gurney">GURNEY, R, EMMETT, B, MCDONALD, A, BLAIR, G, BUYTAERT, W, FREER, J E, HAYGARTH, P, REES, G, TETZLAFF, D and EVO SCIENCE TEAM. The Environmental Virtual Observatory: A New Vision for Catchment Science. American Geophysical Union Fall Meeting 2011. </ref>). The system is designed to promote feedback, ownership, community involvement, and better communication between technical ad non-technical users (EVO 2013<ref name="EVO"></ref>). An example of a community tool established within EVO is The Local Landscape Visualisation Tool, developed by engaging stakeholders in three catchments in the UK: the Afon Dyfi, the River Tarland, and the River Eden (Wilkinson et al., 2013<ref name="Wilkinson">WILKINSON, M, BEVEN, K, BREWER, P, EL-KHATIB, Y, GEMMELL, A, HAYGARTH, P, MACKAY, E, MACKLIN, M, MARSHALL, K, QUINN, P, STUTTER, M., THOMAS, N & VITOLO, C. The Environmental Virtual Observatory (EVO) local exemplar: A cloud based local landscape learning visualisation tool for communicating flood risk to catchment stakeholders. EGU General Assembly 2013 Vienna Austria. </ref>). The tool is accessed via a web portal and communicates flood risk in the local impacted communities. It is based on a number of services, i.e.: catchment datasets, hydrological models, and visualisation tools. Users can access real time data concerning river levels, rainfall, weather, and water quality, which is additionally supported by webcam images, or can use cloud-based models to explore how different land management strategies might affect the risk of flooding (Wilkinson et al., 2013<ref name="Wilkinson"></ref>).		Another technology that could potentially be harnessed for building decision support systems is cloud computing. Environmental Virtual Observatory (EVO) pilot project, sponsored by the UK’s Natural Environment Research Council (NERC), employs cloud computing to integrate datasets, models and tools for cost-effective, efficient and transparent environmental monitoring and decision making (EVO 2013<ref name="EVO">EVO 2013. ''Environmental Virtual Observatory Website ''[Online]. [cited 14 November 2013]. Available: [http://www.evo-uk.org/ http://www.evo-uk.org/.]</ref>). EVO works with other international partners (e.g.: CUAHSI, NeON) to develop consistent standards for exchanging data and models (EVO 2013<ref name="EVO"></ref>). The project activities include developing cyber infrastructure, cloud-enabled environmental models, and a number of exemplar web-based services concerning soil and water management at both local and national scales (EVO 2013<ref name="EVO"></ref>). Exemplars developed within the course of the two year pilot project focus on a range of environmental problems, which directly affect the well-being of people in the UK, e.g.: studying national-scale nutrient fate using linked hydrogeological and biochemical models, developing a system to assess the effects of different land management practices on reducing diffuse pollution from agriculture, advancing modelling capabilities for drought and flood predictions to address and mitigate the effects of climate change, or establishing technologies for studying biodiversity and ecosystem service sustainability (EVO 2013<ref name="EVO"></ref>). EVO aims to provide different groups of users, from scientists to local stakeholders, with free and easy access to expert knowledge by combining assets from various sources with novel tools for data analysis and visualisation (Gurney et al., 2011<ref name="Gurney">GURNEY, R, EMMETT, B, MCDONALD, A, BLAIR, G, BUYTAERT, W, FREER, J E, HAYGARTH, P, REES, G, TETZLAFF, D and EVO SCIENCE TEAM. The Environmental Virtual Observatory: A New Vision for Catchment Science. American Geophysical Union Fall Meeting 2011. </ref>). The system is designed to promote feedback, ownership, community involvement, and better communication between technical ad non-technical users (EVO 2013<ref name="EVO"></ref>). An example of a community tool established within EVO is The Local Landscape Visualisation Tool, developed by engaging stakeholders in three catchments in the UK: the Afon Dyfi, the River Tarland, and the River Eden (Wilkinson et al., 2013<ref name="Wilkinson">WILKINSON, M, BEVEN, K, BREWER, P, EL-KHATIB, Y, GEMMELL, A, HAYGARTH, P, MACKAY, E, MACKLIN, M, MARSHALL, K, QUINN, P, STUTTER, M., THOMAS, N & VITOLO, C. The Environmental Virtual Observatory (EVO) local exemplar: A cloud based local landscape learning visualisation tool for communicating flood risk to catchment stakeholders. EGU General Assembly 2013 Vienna Austria. </ref>). The tool is accessed via a web portal and communicates flood risk in the local impacted communities. It is based on a number of services, i.e.: catchment datasets, hydrological models, and visualisation tools. Users can access real time data concerning river levels, rainfall, weather, and water quality, which is additionally supported by webcam images, or can use cloud-based models to explore how different land management strategies might affect the risk of flooding (Wilkinson et al., 2013<ref name="Wilkinson"></ref>).

	Last but not least, web services can be used to link different modelling frameworks. Hydrologic studies traditionally did not consider bi-directional interactions between atmosphere and water bodies. However, as the scale of the models increase, the assumption about the lack of feedback between the land surface and the atmosphere may no longer hold and bi-directional coupling becomes important (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Up to date coupling of hydrological and climate models has been hindered by discrepancies between both technologies, namely climate models run on high performance computers while hydrologic models run on personal computers (Goodall et al., 2013<ref name="Goodall 2013"></ref>, Saint and Murphy 2010<ref name="Saint"></ref>). Additionally, there is a lack of established techniques for transferring data between differing spatial scales of climate and hydrologic models (Goodall et al., 2013<ref name="Goodall 2011"></ref>). Hydrological Modelling for Assessing Climate Change Impacts at different Scales project (HYACINTS) coupled climate model HIRHAM and physically distributed hydrological model MIKE SHE for the whole of Denmark by migrating both models into the OpenMI standard (HYACINTS 2013<ref name="Hyacints>HYACINTS 2013. ''Hydrological Modelling for Assessing Climate Change Impacts at different Scales Project Website ''[Online]. Last revised 26 June 2009. [cited 14 November 2013]. Available: [http://hyacints.dk/main_uk/main.html http://hyacints.dk/main_uk/main.html.]</ref>). Method based on statistical downscaling and bias-correction was developed to enable data transfer across different grids (HYACINTS 2013<ref name="Hyacints"></ref>). While the project achieved integration of models from different domains, this required migrating them to the same standard. Goodall et al., (2013)<ref name="Goodall 2013"></ref> proposed a novel approach to loosely couple climate and hydrologic models using web services, which enabled integration of different modelling frameworks. The researchers did not address the problem of data scalability between climate and hydrologic models but merely aimed to develop technically feasible strategy for coupling such models. In the proposed approach web services are used to pass data between a hydrologic model running on desktop computer and a climate/weather model running in HPC environment (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The prototype developed in the study was a two-way coupled system composed of the Community Atmosphere Model (CAM) and the Soil and Water Assessment Tool (SWAT) (Goodall et al., 2013<ref name="Goodall 2013"></ref>). CAM implemented with ESMF was made available as a web service. SWAT was provided as an OpenMI compliant model and CAM model was wrapped with an OpenMI interface (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The execution was controlled and implemented by OpenMI’s Configuration Editor (Saint and Murphy 2010<ref name="Saint"></ref>). This study proved that coupling of two disparate modelling systems is feasible while still maintaining the models' original structure and purpose (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The study provided a technical solution for coupling models running on different computing platforms, e.g.: PC and HPC, different HPCs, or cloud (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Bridging the gap between OpenMI and ESMF was possible due to features that both standards provide, namely: ESMF supporting web services and OpenMI supporting a wrapper for accessing external services (Goodall et al., 2013). Both frameworks are widely used within their respective communities and their integration is an important milestone in modelling coupled hydrology-climate systems (Saint and Murphy 2010<ref name="Saint"></ref>).		Last but not least, web services can be used to link different modelling frameworks. Hydrologic studies traditionally did not consider bi-directional interactions between atmosphere and water bodies. However, as the scale of the models increase, the assumption about the lack of feedback between the land surface and the atmosphere may no longer hold and bi-directional coupling becomes important (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Up to date coupling of hydrological and climate models has been hindered by discrepancies between both technologies, namely climate models run on high performance computers while hydrologic models run on personal computers (Goodall et al., 2013<ref name="Goodall 2013"></ref>, Saint and Murphy 2010<ref name="Saint"></ref>). Additionally, there is a lack of established techniques for transferring data between differing spatial scales of climate and hydrologic models (Goodall et al., 2013<ref name="Goodall 2011"></ref>). Hydrological Modelling for Assessing Climate Change Impacts at different Scales project (HYACINTS) coupled climate model HIRHAM and physically distributed hydrological model MIKE SHE for the whole of Denmark by migrating both models into the OpenMI standard (HYACINTS 2013<ref name="Hyacints">HYACINTS 2013. ''Hydrological Modelling for Assessing Climate Change Impacts at different Scales Project Website ''[Online]. Last revised 26 June 2009. [cited 14 November 2013]. Available: [http://hyacints.dk/main_uk/main.html http://hyacints.dk/main_uk/main.html.]</ref>). Method based on statistical downscaling and bias-correction was developed to enable data transfer across different grids (HYACINTS 2013<ref name="Hyacints"></ref>). While the project achieved integration of models from different domains, this required migrating them to the same standard. Goodall et al., (2013)<ref name="Goodall 2013"></ref> proposed a novel approach to loosely couple climate and hydrologic models using web services, which enabled integration of different modelling frameworks. The researchers did not address the problem of data scalability between climate and hydrologic models but merely aimed to develop technically feasible strategy for coupling such models. In the proposed approach web services are used to pass data between a hydrologic model running on desktop computer and a climate/weather model running in HPC environment (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The prototype developed in the study was a two-way coupled system composed of the Community Atmosphere Model (CAM) and the Soil and Water Assessment Tool (SWAT) (Goodall et al., 2013<ref name="Goodall 2013"></ref>). CAM implemented with ESMF was made available as a web service. SWAT was provided as an OpenMI compliant model and CAM model was wrapped with an OpenMI interface (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The execution was controlled and implemented by OpenMI’s Configuration Editor (Saint and Murphy 2010<ref name="Saint"></ref>). This study proved that coupling of two disparate modelling systems is feasible while still maintaining the models' original structure and purpose (Goodall et al., 2013<ref name="Goodall 2013"></ref>). The study provided a technical solution for coupling models running on different computing platforms, e.g.: PC and HPC, different HPCs, or cloud (Goodall et al., 2013<ref name="Goodall 2013"></ref>). Bridging the gap between OpenMI and ESMF was possible due to features that both standards provide, namely: ESMF supporting web services and OpenMI supporting a wrapper for accessing external services (Goodall et al., 2013). Both frameworks are widely used within their respective communities and their integration is an important milestone in modelling coupled hydrology-climate systems (Saint and Murphy 2010<ref name="Saint"></ref>).

	==References==		==References==

	[[category:OR/14/022 Couplers for linking environmental models: Scoping study and potential next steps \| 03]]		[[category:OR/14/022 Couplers for linking environmental models: Scoping study and potential next steps \| 03]]