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Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models

机译:通过交互式生态平台实现生态预报,将数据(EcoPad,V1.0)和模型分化为模型

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Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models. EcoPAD (v1.0) is a web-based software system that automates data transfer and processing from sensor networks to ecological forecasting through data management, model simulation, data assimilation, forecasting, and visualization. It facilitates interactive data–model integration from which the model is recursively improved through updated data while data are systematically refined under the guidance of model. EcoPAD (v1.0) relies on data from observations, process-oriented models, DA techniques, and the web-based workflow. We applied EcoPAD (v1.0) to the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in northern Minnesota. The EcoPAD-SPRUCE realizes fully automated data transfer, feeds meteorological data to drive model simulations, assimilates both manually measured and automated sensor data into the Terrestrial ECOsystem (TECO) model, and recursively forecasts the responses of various biophysical and biogeochemical processes to five temperature and two CO2 treatments in near-real time (weekly). Forecasting with EcoPAD-SPRUCE has revealed that mismatches in forecasting carbon pool dynamics are more related to model (e.g., model structure, parameter, and initial value) than forcing variables, opposite to forecasting flux variables. EcoPAD-SPRUCE quantified acclimations of methane production in response to warming treatments through shifted posterior distributions of the CH4:CO2 ratio and the temperature sensitivity (Q10) of methane production towards lower values. Different case studies indicated that realistic forecasting of carbon dynamics relies on appropriate model structure, correct parameterization, and accurate external forcing. Moreover, EcoPAD-SPRUCE stimulated active feedbacks between experimenters and modelers to identify model components to be improved and additional measurements to be taken. It has become an interactive model–experiment (ModEx) system and opens a novel avenue for interactive dialogue between modelers and experimenters. Altogether, EcoPAD (v1.0) acts to integrate multiple sources of information and knowledge to best inform ecological forecasting.
机译:预测生态系统服务的未来变化不仅是非常理想的,而且还变得可行,因为若干力量(例如,可用的大数据,开发的数据同化(DA)技术和先进的网络 - 基础设施)正在融合,以将生态研究转化为定量预测。为了实现生态预测,我们开发了一个用于将数据(EcoPad,V1.0)的生态平台进入模型。 Ecopad(v1.0)是一种基于Web的软件系统,通过数据管理,模型模拟,数据同化,预测和可视化自动化传感器网络的数据传输和处理。它促进了通过更新数据递归地改善模型的交互式数据模型集成,而在模型的指导下系统地精制数据。 Ecopad(v1.0)依赖于观察,面向过程的模型,DA技术和基于Web的工作流程的数据。我们在明尼苏达州北部的气候和环境变化(云杉)实验中申请了Ecopad(v1.0)到云杉和泥炭地反应。 EcoPad-云杉实现全自动数据传输,将气象数据馈送到驱动模型模拟,使手动测量和自动传感器数据同化到地面生态系统(TECO)模型,并递归地预测各种生物物理和生物地态化过程的反应至五个温度和近乎实时的两种CO2治疗(每周)。与Ecopad-Spruce的预测揭示了预测碳池动态的不匹配与模型(例如,模型结构,参数和初始值)更相关,而不是强制变量与预测通量变量相反。 ECOPAD-HERUCE响应于温热处理通过偏移的CH4:CO 2:CO 2的偏移和甲烷产生的温度敏感性(Q10)朝向较低值的温度敏感性(Q10)来定量甲烷产生的适应性。不同的案例研究表明,碳动力学的现实预测依赖于适当的模型结构,正确的参数化和准确的外部强制。此外,EcoPad-Spruce刺激了实验者和建模者之间的积极反馈,以识别要改进的模型组分和额外的测量。它已成为一个交互式模型 - 实验(Modex)系统,并在建模者和实验者之间开设一个新颖的互动对话。共有Ecopad(v1.0)的行为使多个信息和知识来源集成,以最好地通知生态预测。

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