A two-stage inflation method in parameter estimation to compensate for constant parameter evolution in CESM
A two-stage inflation method in parameter estimation to compensate for constant parameter evolution in CESM
复制标题
补偿CESM中常数参数演化的参数估计中的两阶段膨胀方法
DOI：
10.1007/s13131-021-1856-5
复制
发表时间：
2022
影响因子：
1.4
通讯作者：
Tang Youmin
中科院分区：
文献类型：
--
作者：
Shen Zheqi;Tang Youmin
参数估计是利用观测值对模型参数进行调整或优化的过程。基于集成的参数估计方法中的一个长期问题是在模型集成期间假设参数是恒定的。这一假设会导致参数系综传播的低估，从而导致参数系综在找到最优解之前趋于崩溃，在这项工作中，一个两阶段的膨胀方法被开发用于参数估计，它可以解决由于参数的不断演变的参数系综崩溃。在第一阶段中，自适应膨胀被施加到增广状态，其中全局标量参数被转换为具有空间依赖性的场。在第二阶段，额外的乘法膨胀被用来膨胀的标量参数系综，以补偿常数参数的演变，其中的膨胀因子是根据模型状态的蔓延增长率。利用共同体地球系统模式（CESM）进行的观测系统模拟实验表明，膨胀方案的第二阶段对参数估计的成功起着至关重要的作用。通过适当的乘性膨胀因子，参数估计可以有效地降低参数偏差，提供更准确的分析。
Parameter estimation is defined as the process to adjust or optimize the model parameter using observations. A long-term problem in ensemble-based parameter estimation methods is that the parameters are assumed to be constant during model integration. This assumption will cause underestimation of parameter ensemble spread, such that the parameter ensemble tends to collapse before an optimal solution is found. In this work, a two-stage inflation method is developed for parameter estimation, which can address the collapse of parameter ensemble due to the constant evolution of parameters. In the first stage, adaptive inflation is applied to the augmented states, in which the global scalar parameter is transformed to fields with spatial dependence. In the second stage, extra multiplicative inflation is used to inflate the scalar parameter ensemble to compensate for constant parameter evolution, where the inflation factor is determined according to the spread growth ratio of model states. The observation system simulation experiment with Community Earth System Model (CESM) shows that the second stage of the inflation scheme plays a crucial role in successful parameter estimation. With proper multiplicative inflation factors, the parameter estimation can effectively reduce the parameter biases, providing more accurate analyses.