Collaborative Research: CSEDI--Variational Approaches to Geomagnetic Data Assimilation

该项目的目标是开发方法，结合历史和正在进行的测量地球？的磁场与地球的数值计算机模型？的动态核心，在那里产生的地磁场。 类似的方法，通常被称为数据同化（DA），被广泛用于大气科学，以提高由大气流动的数值模式生成的天气预报的可靠性。 我们的应用这些方法的地磁场将允许改进模型的磁场产生的发展，更好地了解地球的物理过程？的核心，并改善估计的缓慢时间变化的地磁场，即地磁长期变化（SV）的历史和更遥远的过去。 这种改进的SV将在各种科学研究中具有价值，包括地球自转，地球动力学，地磁和古气候。 最终，地磁DA的发展将导致改善地球未来演变的预测？该项目建立在以前的工作与顺序DA地磁，适应最近的发展变化DA方法在海洋和大气科学。 我们的努力的关键组成部分包括开发的MoSST（模块化可扩展自洽三维）geodynamo模型的切线线性和伴随代码，使用这些代码来实现现代变分DA计划（所谓的代表方法），并初步应用到地磁数据集。在变分方法模式输入（初始和边界数据，强迫）进行调整，同时适合动力学方程和观测数据。 这种技术方法提供了一种自然的方式来使用近年来的高质量数据来改善过去时期的磁场和核心流估计，从而允许动态一致地同时估计核心中的磁场和流体速度场的时间演变以及在表面处可观察到的结果信号。更一般地说，变分DA提供了一个共同的框架，比较地球发电机模型的输出数据，并允许严格的测试动力学假设。 为变分DA开发的切线线性和伴随工具也将应用于数值地球发电机模型的灵敏度和稳定性分析。

The objective of this project is to develop methods for combining historical and ongoing measurements of the Earth?s magnetic field with numerical computer models for Earth?s dynamic core, where the geomagnetic field is generated. Similar methods, generally referred to as data assimilation (DA), are widely used in atmospheric sciences to improve reliability of weather forecasts generated by numerical models of atmospheric flows. Our application of these methods to the geomagnetic field will allow development of improved models of magnetic field generation, better understanding of physical processes in Earth?s core, and improved estimation of the slow time variations of the geomagnetic field, i.e. geomagnetic secular variation (SV) in the historical and more distant past. Such improved SV will be of value in diverse scientific studies, including Earth rotation, geodynamics, geomagnetism, and paleoclimate. Ultimately, development of geomagnetic DA will result in improved forecasts of the future evolution of the Earth?s magnetic field.The project builds on previous work with sequential DA in geomagnetism, adapting recent developments of variational DA methods in ocean and atmospheric sciences. Key components of our effort include development of tangent linear and adjoint codes for the MoSST (Modular Scalable Self-consistent Three-dimensional) geodynamo model, use of these codes to implement a modern variational DA scheme (the so-called representer method), and initial applications to geomagnetic datasets. In the variational approach model inputs (initial and boundary data, forcing) are adjusted to simultaneously fit dynamical equations and observational data. This technical approach provides a natural way to use high quality data from recent years to improve magnetic field and core flow estimates for past epochs, allowing dynamically consistent simultaneous estimation of the time evolution of the magnetic and fluid velocity fields in the core, and the resulting signals observable at the surface. More generally, variational DA provides a common framework for comparing geodynamo model outputs to data, and will allow rigorous tests of dynamical hypotheses. The tangent linear and adjoint tools developed for variational DA will also have applications to sensitivity and stability analysis of the numerical geodynamo models.