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Direct Measurement of Earth’s Energy Imbalance with Geodetic Satellites – Feasibility Study (EEI-Geodetic)

Direct Measurement of Earth’s Energy Imbalance with Geodetic Satellites – Feasibility Study (EEI-Geodetic)
利用大地测量卫星直接测量地球能量不平衡 – 可行性研究 (EEI-Geodetic)
批准号:
441179229
负责人:
Professor Dr.-Ing. Jürgen Kusche
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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中文摘要
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英文摘要
Earth’s Energy Imbalance (EEI) represents the difference between the energy absorbed and emitted by the Earth at the top of the atmosphere. Its long-term global mean is currently estimated to <0.9 W/m2. Several recent studies have pointed out the need to measure mean EEI with an accuracy of 0.1 W/m2 at larger spatial scales, and to detect possible long-term temporal changes. EEI at the top of the atmosphere is currently observed with the CERES family of satellite radiometers, but these sensors are known to have calibration problems at long timescales, so their mean has been anchored inestimates from ocean data. However, estimates of ocean heat change have their own problems due to sparsity of in-situ data such as Argo. Here we suggest to derive EEI from either indirect observation of solar and Earth’s radiation pressure with accelerometers or from satellite laser ranging. This is a very challenging objective, since it is not clear which accuracy the existing geodetic data base will allow for, and at which temporal and spatial resolution. We will develop a simulation framework that will enable testing and optimizing a dedicated EEI geodetic satellite, a constellation of such, or a future gravity mission such as GRACE-II equipped with improved accelerometers. The goal would be to validate, and possibly improve, the CERES-based estimates at large spatial scales (global mean,land-ocean-arctic partitioned, latitudinal bands) and at annual and longer timescales
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会议论文
Developing an Ensemble Kalman Filter calibration and data assimilation (EnC/DA) approach for integrating geodetic and remote sensing data into a global hydrological model
Developing a Stabilized Ensemble Kalman Filter for integrating daily GRACE/GRACE-FO data into process models (S-ENKF)
Bayesian Methods in Geodetic Earth System Research
Lunar Reference Systems
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海外基金
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: