Cenlin He, Prasanth Valayamkunnath, M. Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, D. Niyogi, Michael Ek
{"title":"通过多参数化选项(Noah MP)实现开源社区Noah的现代化陆地表面模型(版本5.0),增强了模块性、互操作性和适用性","authors":"Cenlin He, Prasanth Valayamkunnath, M. Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, D. Niyogi, Michael Ek","doi":"10.5194/gmd-16-5131-2023","DOIUrl":null,"url":null,"abstract":"Abstract. The widely used open-source community Noah with multi-parameterization options (Noah-MP) land surface model (LSM) is\ndesigned for applications ranging from uncoupled land surface\nhydrometeorological and ecohydrological process studies to coupled numerical\nweather prediction and decadal global or regional climate simulations. It has\nbeen used in many coupled community weather, climate, and hydrology models. In\nthis study, we modernize and refactor the Noah-MP LSM by adopting modern Fortran\ncode standards and data structures, which substantially enhance the model\nmodularity, interoperability, and applicability. The modernized Noah-MP is\nreleased as the version 5.0 (v5.0), which has five key features: (1) enhanced modularization as a result of re-organizing model physics into individual\nprocess-level Fortran module files, (2) an enhanced data structure with new\nhierarchical data types and optimized variable declaration and\ninitialization structures, (3) an enhanced code structure and calling workflow\nas a result of leveraging the new data structure and modularization, (4) enhanced\n(descriptive and self-explanatory) model variable naming standards, and (5) enhanced driver and interface structures to be coupled with the host\nweather, climate, and hydrology models. In addition, we create a comprehensive\ntechnical documentation of the Noah-MP v5.0 and a set of model benchmark and\nreference datasets. The Noah-MP v5.0 will be coupled to various\nweather, climate, and hydrology models in the future. Overall, the modernized\nNoah-MP allows a more efficient and convenient process for future model\ndevelopments and applications.\n","PeriodicalId":12799,"journal":{"name":"Geoscientific Model Development","volume":" ","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability\",\"authors\":\"Cenlin He, Prasanth Valayamkunnath, M. Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, D. Niyogi, Michael Ek\",\"doi\":\"10.5194/gmd-16-5131-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. The widely used open-source community Noah with multi-parameterization options (Noah-MP) land surface model (LSM) is\\ndesigned for applications ranging from uncoupled land surface\\nhydrometeorological and ecohydrological process studies to coupled numerical\\nweather prediction and decadal global or regional climate simulations. It has\\nbeen used in many coupled community weather, climate, and hydrology models. In\\nthis study, we modernize and refactor the Noah-MP LSM by adopting modern Fortran\\ncode standards and data structures, which substantially enhance the model\\nmodularity, interoperability, and applicability. The modernized Noah-MP is\\nreleased as the version 5.0 (v5.0), which has five key features: (1) enhanced modularization as a result of re-organizing model physics into individual\\nprocess-level Fortran module files, (2) an enhanced data structure with new\\nhierarchical data types and optimized variable declaration and\\ninitialization structures, (3) an enhanced code structure and calling workflow\\nas a result of leveraging the new data structure and modularization, (4) enhanced\\n(descriptive and self-explanatory) model variable naming standards, and (5) enhanced driver and interface structures to be coupled with the host\\nweather, climate, and hydrology models. In addition, we create a comprehensive\\ntechnical documentation of the Noah-MP v5.0 and a set of model benchmark and\\nreference datasets. The Noah-MP v5.0 will be coupled to various\\nweather, climate, and hydrology models in the future. Overall, the modernized\\nNoah-MP allows a more efficient and convenient process for future model\\ndevelopments and applications.\\n\",\"PeriodicalId\":12799,\"journal\":{\"name\":\"Geoscientific Model Development\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2023-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoscientific Model Development\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/gmd-16-5131-2023\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscientific Model Development","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/gmd-16-5131-2023","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability
Abstract. The widely used open-source community Noah with multi-parameterization options (Noah-MP) land surface model (LSM) is
designed for applications ranging from uncoupled land surface
hydrometeorological and ecohydrological process studies to coupled numerical
weather prediction and decadal global or regional climate simulations. It has
been used in many coupled community weather, climate, and hydrology models. In
this study, we modernize and refactor the Noah-MP LSM by adopting modern Fortran
code standards and data structures, which substantially enhance the model
modularity, interoperability, and applicability. The modernized Noah-MP is
released as the version 5.0 (v5.0), which has five key features: (1) enhanced modularization as a result of re-organizing model physics into individual
process-level Fortran module files, (2) an enhanced data structure with new
hierarchical data types and optimized variable declaration and
initialization structures, (3) an enhanced code structure and calling workflow
as a result of leveraging the new data structure and modularization, (4) enhanced
(descriptive and self-explanatory) model variable naming standards, and (5) enhanced driver and interface structures to be coupled with the host
weather, climate, and hydrology models. In addition, we create a comprehensive
technical documentation of the Noah-MP v5.0 and a set of model benchmark and
reference datasets. The Noah-MP v5.0 will be coupled to various
weather, climate, and hydrology models in the future. Overall, the modernized
Noah-MP allows a more efficient and convenient process for future model
developments and applications.
期刊介绍:
Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication:
* geoscientific model descriptions, from statistical models to box models to GCMs;
* development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results;
* new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data;
* papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data;
* model experiment descriptions, including experimental details and project protocols;
* full evaluations of previously published models.