Feasibility study of a time-mean Earth energy imbalance estimate derived from Satellite Laser Ranging measurement of the Earth Radiation Pressure

Accurate measurement of Earth’s energy imbalance (EEI) is one of the central challenges in climate science.  At present, global and regional EEI variability is inferred from radiometric measurements, anchored with time-mean planetary energy inventory estimates due to sensor absolute calibration biases. Space dynamics methods for EEI estimation have been investigated since the 1970s, notably with the CASTOR/CACTUS accelerometers, whose performance exceeded expectations. It led to the BIRAMIS project which aimed at directly measuring EEI from accelerometer observations of the Earth Radiation Pressure (ERP).

In this study, we investigate an alternative space-dynamics–based approach to infer time-mean EEI and anchor CERES. The method aims to provide an alternative anchoring method by directly correcting the absolute calibration error of the CERES radiometers with the introduction of an adjustable scaling parameter applied to the ERP acting on passive spherical satellites tracked by Satellite Laser Ranging (SLR). This method is expected to substantially improve the accuracy of CERES observations, reducing the current accuracy of ±2.5 W.m-2 over a decadal timescale to a target accuracy of a few 0.1 W.m-2 on an annual basis. 

To assess the accuracy of this method, we focus on Ajisai, a Japanese geodetic satellite launched in 1986. Ajisai is a suitable candidate due to its altitude of approximately 1500 km, its area-to-mass ratio, which is nearly an order of magnitude larger than that of most other geodetic satellites, and its spin-stabilized configuration. To evaluate the feasibility and relevance of the approach, we simulate SLR observations, allowing us to introduce controlled errors both in the measurements and in the force models.

In this study we account for error sources from gravity field and tidal models, atmospheric drag, the Yarkovsky effect, SLR measurement noise, and station-related errors. As expected, the results show that the estimate of the time-mean EEI is primarily affected by uncertainties in atmospheric drag and the Yarkovsky effect. A parameter sensitivity study was conducted to identify optimal strategies for mitigating these errors. The time-mean EEI estimate is also sensitive to anisotropic effects arising from Ajisai’s non-perfect spherical symmetry, which introduce a non-negligible bias.

Overall, we establish an error budget for this new method and demonstrate the estimate of the time-mean EEI from SLR measurement is feasible. The quantitative results suggest this approach could be sufficiently precise to anchor CERES at a better precision than currently done with the planetary inventory.