讲座题目：Matrix approach to facilitate land carbon modeling: Case studies with CLM45 and ORCHIDEE-MICT
主讲人：Dr. Yuanyuan Huang
主持人：夏建阳 副教授
开始时间：2018-01-05 （周五）10:00
讲座地址：闵行校区 资环楼435会议室
主办单位：beat365 科技处
报告人简介：
Dr. Yuanyuan Huang works as a postdoctoral researcher at Le Laboratoire des Sciences du Climat et de l'Environnement, France. Her research focuses on understanding and modeling terrestrial biogeochemical cycles. She received her Ph.D. degree from University of Florida, where she developed the nitrous oxide (N2O) emission model and quantified terrestrial N2O dynamics through Geophysical Fluid Dynamics Laboratory (GFDL)’s land carbon-nitrogen model LM3V-N. Later on, she developed matrix equations for the land surface model CLM from the National Center for Atmospheric Research, USA and for ORCHIDEE from the Institut Pierre Simon Laplace, France. She is also the developer of the snow and soil thermal dynamic module embedded in the Terrestrial ECOsystem (TECO) model. She is actively involved in applying data assimilation techniques in land modeling and is currently working with the ORCHIDEE Data Assimilation System to better represent the simulation of carbon, nitrogen and phosphorus in terrestrial ecosystems.
报告内容简介：
The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but is computationally expensive and complex, limiting the modeling community to conduct comprehensive parametric sensitivity analyses, track model behavior and benchmark model responses. To overcome these challenges, I developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. I applied the matrix approach to the Community Land Model (CLM4.5) and ORCHIDEE-MICT with vertically resolved biogeochemistry. In this talk, I will illustrate that the matrix equation exactly reproduces litter and soil organic carbon dynamics in the original ESMs. The matrix approach allows flexible sensitivity assessments, enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to detailed processes. In addition, the matrix tool can be potentially used to accelerate model spin-up, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.
