气候变化领域集成服务门户(CCPortal): Making Ecosystem Modeling Operational-A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories

CCPortal

DOI	10.1029/2023EF004295
	Making Ecosystem Modeling Operational-A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories
	Steenbeek, Jeroen; Ortega, Pablo; Bernardello, Raffaele; Christensen, Villy; Coll, Marta; Exarchou, Eleftheria; Fuster-Alonso, Alba; Heneghan, Ryan; Melis, Laura Julia; Pennino, Maria Grazia; Rivas, David; Keenlyside, Noel
发表日期	2024
EISSN	2328-4277
起始页码	12
结束页码	3
卷号	12 期号:3
英文摘要	Marine Ecosystem Models (MEMs) are increasingly driven by Earth System Models (ESMs) to better understand marine ecosystem dynamics, and to analyze the effects of alternative management efforts for marine ecosystems under potential scenarios of climate change. However, policy and commercial activities typically occur on seasonal-to-decadal time scales, a time span widely used in the global climate modeling community but where the skill level assessments of MEMs are in their infancy. This is mostly due to technical hurdles that prevent the global MEM community from performing large ensemble simulations with which to undergo systematic skill assessments. Here, we developed a novel distributed execution framework constructed of low-tech and freely available technologies to enable the systematic execution and analysis of linked ESM/MEM prediction ensembles. We apply this framework on the seasonal-to-decadal time scale, and assess how retrospective forecast uncertainty in an ensemble of initialized decadal ESM predictions affects a mechanistic and spatiotemporal explicit global trophodynamic MEM. Our results indicate that ESM internal variability has a relatively low impact on the MEM variability in comparison to the broad assumptions related to reconstructed fisheries. We also observe that the results are also sensitive to the ESM specificities. Our case study warrants further systematic explorations to disentangle the impacts of climate change, fisheries scenarios, MEM internal ecological hypotheses, and ESM variability. Most importantly, our case study demonstrates that a simple and free distributed execution framework has the potential to empower any modeling group with the fundamental capabilities to operationalize marine ecosystem modeling. Climate change and human activities like fishing are affecting the balance of marine ecosystems and the services they provide. To understand impacts better, scientists use computer models that consider climate, ocean conditions, and ocean life. To make robust decisions, decision makers need robust science delivered by robust models. This requires running many computer simulations, but the complexity of marine ecosystems models makes this difficult. Typically, only institutions with sufficient financial and technical means can overcome these difficulties, which leaves the majority of marine ecosystem modelers wanting. Here we introduce a possible solution to overcome the difficulties, using only simple and free technologies to facilitate the systematic execution of complex ecosystem models across networks of computers, to allow any modeling group to perform these exercises. We demonstrate our solution by running a global marine ecosystem model, EcoOcean, hundreds of times to see how it is affected by variability in ocean conditions. Using available laptops and desktops, we can now complete this task in 30 hr; where prior this modeling task would have taken weeks to complete. It is conceptually simple solutions such as these that may make the process of marine ecosystem modeling easier and more operational around the globe, thus opening the door for scientific management breakthroughs. Most marine ecosystem modellers lack the skills and resources to systematically calibrate, validate and assess the models for uncertainty Here we present a low-tech and open source run framework to use any computer network as a distributed model execution and assessment system We use the framework to mass-execute an Earth System/Ecosystem Model ensemble to assess the ecosystem impact of ESM uncertainty
英文关键词	marine ecosystem models; systematic assessments; distributed execution; open-source software; MacGyver
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Meteorology & Atmospheric Sciences
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:001180261700001
来源期刊	EARTHS FUTURE
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/290787
作者单位	Universitat Politecnica de Catalunya; Barcelona Supercomputer Center (BSC-CNS); Consejo Superior de Investigaciones Cientificas (CSIC); CSIC - Centro Mediterraneo de Investigaciones Marinas y Ambientales (CMIMA); CSIC - Instituto de Ciencias del Mar (ICM); Queensland University of Technology (QUT); Spanish Institute of Oceanography; University of Bergen; Bjerknes Centre for Climate Research; CICESE - Centro de Investigacion Cientifica y de Educacion Superior de Ensenada; Nansen Environmental & Remote Sensing Center (NERSC)
推荐引用方式 GB/T 7714	Steenbeek, Jeroen,Ortega, Pablo,Bernardello, Raffaele,et al. Making Ecosystem Modeling Operational-A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories[J],2024,12(3).
APA	Steenbeek, Jeroen.,Ortega, Pablo.,Bernardello, Raffaele.,Christensen, Villy.,Coll, Marta.,...&Keenlyside, Noel.(2024).Making Ecosystem Modeling Operational-A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories.EARTHS FUTURE,12(3).
MLA	Steenbeek, Jeroen,et al."Making Ecosystem Modeling Operational-A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories".EARTHS FUTURE 12.3(2024).