Data Assimilation in Atmospheric Sciences

PI Jan Mandel将在NCAR居住一学年，研究大气科学，并在飓风和野火模型中进行数据同化研究。在以往的研究中，他主要建立了一种基于物理和偏微分方程的野火模型，并开发了新的数据同化方法，适用于高度非线性问题。该项目的目的是通过与中尺度气象学和数据同化方面的一些最好的专家进行互动和合作，获得所需的大气科学背景和实践经验。PI还将学习如何使用和扩展WRF（天气研究预报）大气模型代码，并将他的方法与WRF一起用于实际数据源。野火和飓风等灾难性天气事件给人类活动带来的风险是巨大的。新的数据同化方法将有助于更好的及时预报，从而节省生命和财产。它们还可以改进对环境传感器数据的使用和解释，这些数据正变得广泛可用，以便对自然灾害或基于大气污染物的恐怖袭击提供早期准确的预警。该项目将涉及PI的两名博士生，他们目前正在研究与数据同化和野火建模相关的论文主题。学生们将定期访问NCAR，与PI一起工作并参加研讨会。项目获得的新知识将使学生的论文研究与大气科学的应用相结合，并使项目能够更有效地监督学生的研究。该IGMS项目由MPS多学科活动办公室（OMA）和数学科学司（DMS）联合支持。

Jan Mandel, PI, will spend one academic year in residence at NCAR to study atmospheric science and perform research in data assimilation in hurricane and wildfire modeling. In previous research, he has taken the principal role in building a new wildfire model based on physics and partial differential equations and developed new data assimilation methods, suitable for highly nonlinear problems. The purpose of this project is to gain the needed background and hands-on experience in atmospheric sciences, in interaction and collaboration with some of the best experts in mesoscale meteorology and data assimilation. The PI will also learn how to work with and extend the WRF (Weather Research Forecasting) atmospheric model code, and to use his methods with WRF on real data sources.Risks to human activities from catastrophic weather related events such as wildfires and hurricanes are immense. The new data assimilation methods will contribute to better on time forecasts and thus savings in lives and property. They can also improve the use and interpretation of data from environmental sensors, which are becoming widely available, to provide an early and accurate warning of a natural disaster or an atmospheric contaminant based terrorist attack. The project will involve two of the PI's PhD students, whoare currently working on thesis topics related to data assimilation and wildfire modeling. The students will regularly visit NCAR to work with the PI and to participate in seminars. The new knowledge gainedby the PI will make it possible to integrate the students' thesis research with applications in atmospheric sciences and it will enable the PI to supervise the students' research more efficiently.This IGMS project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).