Improved STOchastic modelling in GRACE/GRACE-FO REal data processing (ISTORE)

GRACE/GRACE-FO 真实数据处理 (ISTORE) 中改进的 STochastic 建模

• 批准号: 417221075
• 负责人: Dr.-Ing. Rolf König
• 金额: --
• 依托单位: Department 1: Geodäsie
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/417221075?language=en
• 关键词: Improved; STOchastic; modelling; GRACE; FO

One of the main goals of the RU is the assessment of an improved stochastic modelling inGRACE and GRACE-FO temporal gravity field determination. The objective for this IP is to take into account extensive stochastic error characteristics of the central GRACE/GRACE-FO observation types for inter-satellite ranging and accelerometer measurements, and to utilize wide-ranging co-variance information of atmospheric, oceanic and hydrologic background models. With an improved a-priori stochastic model of the estimation process, the ambition is to improve the weighting of all input data (observations and background models) and herewith the estimates of the gravity field parameters and their formal errors. The task will be tackled with a combination of Monte Carlo simulations and linear error propagation theory. Procedures and outcome will be tested and validated using 3 years of GRACE/GRACE-FO real data.

RU的主要目标之一是评估GRACE和GRACE-FO时间重力场确定中改进的随机模型。该IP的目标是考虑到用于卫星间测距和加速度计测量的中央GRACE/GRACE-FO观测类型的广泛随机误差特征，并利用大气、海洋和水文背景模型的大范围协方差信息。利用改进的先验随机模型估计过程，目的是提高所有输入数据(观测值和背景模型)的权重，从而提高重力场参数及其形式误差的估计。这项任务将结合蒙特卡罗模拟和线性误差传播理论来解决。程序和结果将使用3年的GRACE/GRACE-FO真实数据进行测试和验证。