GitHub Actions, a popular CI/CD platform, introduces significant security challenges due to its integration with GitHub’s open ecosystem and its use of flexible workflow configurations. This paper presents Sher, a Py...GitHub Actions, a popular CI/CD platform, introduces significant security challenges due to its integration with GitHub’s open ecosystem and its use of flexible workflow configurations. This paper presents Sher, a Python-based tool that enhances the security of GitHub Actions by automating the detection and remediation of security issues in workflows. Self-Hosted Ephemeral Runner, or Sher, acts as a broker between GitHub’s APIs and a customizable, isolated environment, analyzing workflows through a static rules engine and automatically fixing identified issues. By providing a secure, ephemeral runner environment and a dynamic analysis tool, Sher addresses common misconfigurations and vulnerabilities, contributing to the resilience and integrity of DevSecOps practices within software development pipelines.展开更多
The presence of light-absorbing aerosols （LAA） in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take th...The presence of light-absorbing aerosols （LAA） in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consider- ation. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil on snow. Specifically, the Snow, Ice and Aerosol Radiation Transfer （SAST） model, which includes the impacts of LAA （SNICAR） model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot （SASP）, Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are esti- mated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and ＂snow all gone＂ day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.展开更多
This paper describes a modified version of SSIB through implementing a new snow model (SAST) in Simplified Simple Biosphere Model SSIB for climate study and presents the evaluation results by testing the scheme based ...This paper describes a modified version of SSIB through implementing a new snow model (SAST) in Simplified Simple Biosphere Model SSIB for climate study and presents the evaluation results by testing the scheme based on the field data from Russia and France. The relevant equations in the scheme are given, which describe complicated interactive processes among air-vegetation-snow-soil continuum through mass and heat exchange. An efficient numerical scheme is developed to solve the nonlinear equations successfully. By using the field data from Russia and France, the function of the new scheme is evaluated. The numerical results from the scheme show good agreement with field data. It indicates that the scheme developed here is workable and can be extended for climate study. Key words Snow cover model (SAST) - SSIB - Implementing - Evaluation This work was supported by the foundation from China: 1)NSF Grant 49835010, 2) National key program G1998040900—Part 1, 3) NSF 40075019, 4) NSF 49823002.展开更多
In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study. it is necessary to fully understand the effects of important snow internal processes and interaction with...In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study. it is necessary to fully understand the effects of important snow internal processes and interaction with air and to get an insight into influence of several relevant parameterization schemes with parameters' uncertainty to some degree. Using the snow model (SAST) developed by first author and other one and some useful field observation data, this paper has conducted a series of sensitivity studies on the parameterization schemes. They are relative to compaction process, snow thermal conduction, methodology of layering snow pack and to key parameters such as snow albedo, water holding capacity. Then, based on the results from the sensitivity studies, some useful conclusions for snow cover model improvement are obtained from the analysis of the results.展开更多
文摘GitHub Actions, a popular CI/CD platform, introduces significant security challenges due to its integration with GitHub’s open ecosystem and its use of flexible workflow configurations. This paper presents Sher, a Python-based tool that enhances the security of GitHub Actions by automating the detection and remediation of security issues in workflows. Self-Hosted Ephemeral Runner, or Sher, acts as a broker between GitHub’s APIs and a customizable, isolated environment, analyzing workflows through a static rules engine and automatically fixing identified issues. By providing a secure, ephemeral runner environment and a dynamic analysis tool, Sher addresses common misconfigurations and vulnerabilities, contributing to the resilience and integrity of DevSecOps practices within software development pipelines.
基金supported jointly by projects from the National Natural Science Foundation of China (Grant No.41275003)the National Key Basic Research and Development Projects of China (Grant No.2014CB953903)
文摘The presence of light-absorbing aerosols （LAA） in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consider- ation. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil on snow. Specifically, the Snow, Ice and Aerosol Radiation Transfer （SAST） model, which includes the impacts of LAA （SNICAR） model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot （SASP）, Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are esti- mated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and ＂snow all gone＂ day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.
基金the foundation from China: 1) NSF Grant 49835010, 2) National keyprogram G1998040900-Part 1,3) NSF 40075019, 4) NSF 49823002.
文摘This paper describes a modified version of SSIB through implementing a new snow model (SAST) in Simplified Simple Biosphere Model SSIB for climate study and presents the evaluation results by testing the scheme based on the field data from Russia and France. The relevant equations in the scheme are given, which describe complicated interactive processes among air-vegetation-snow-soil continuum through mass and heat exchange. An efficient numerical scheme is developed to solve the nonlinear equations successfully. By using the field data from Russia and France, the function of the new scheme is evaluated. The numerical results from the scheme show good agreement with field data. It indicates that the scheme developed here is workable and can be extended for climate study. Key words Snow cover model (SAST) - SSIB - Implementing - Evaluation This work was supported by the foundation from China: 1)NSF Grant 49835010, 2) National key program G1998040900—Part 1, 3) NSF 40075019, 4) NSF 49823002.
基金This work is financially supported by 1) National Key Programme for Developing Basic Sciences.G1998040900-Part 1, 2) NSF (key
文摘In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study. it is necessary to fully understand the effects of important snow internal processes and interaction with air and to get an insight into influence of several relevant parameterization schemes with parameters' uncertainty to some degree. Using the snow model (SAST) developed by first author and other one and some useful field observation data, this paper has conducted a series of sensitivity studies on the parameterization schemes. They are relative to compaction process, snow thermal conduction, methodology of layering snow pack and to key parameters such as snow albedo, water holding capacity. Then, based on the results from the sensitivity studies, some useful conclusions for snow cover model improvement are obtained from the analysis of the results.
