The underlying assumptions associated with many of these methods have also constrained their utility and limited the possibilities for data intercomparison.
The obtained calibrated accelerations are validated in several different ways; namely by (i) physically modelled nongravitational forces, by (ii) intercomparison of calibrated accelerometer data from two Swarm satellites flying side-by-side, and by (iii) good agreement of our calibrated signals with those released by ESA, obtained via a different approach for reducing temperature effects.
The LBA data-model intercomparison project (LBA-DMIP) was designed to compare land surface/ecosystem model simulations of terrestrial energy, water and CO2 fluxes with long-term observations of these quantities over Amazonia to provide understanding on how well these models quantify the land surface process, to assess deficiencies in the models and to suggest how they could be improved.
The data from the intercomparison will allow us to compare those protocols that produced excellent accuracy and precision with those that produced poorer accuracy and/or precision for each type of mass spectrometer.
Intercomparison of both versions of data products in the selected grid between 30 31°N and 83 84°E within the study area during 2007 2017 revealed that the VFM and aerosol sub-types are in good agreement of ∼95.27% and ∼82.80%, respectively.
Based on the standard model simulation procedures and consistent input data sets, the intercomparisons will identify and quantify uncertainty sources for various estimates of GHG budgets resulting from different model representations, structures and parameterizations.
Together, these data allow a comprehensive scale intercomparison of remotely sensed predictions, which include intercomparisons of the evapotranspiration products from the various sensors as well as a statistical analysis for the retrievals at the watershed scale.
Our synthesis highlights gaps in the data and challenges for data intercomparison.
Specifically, we first present how to extract crop data from the Agricultural Model Intercomparison and Improvement Project packages, and then develop a method to combine these data with a historical cropland data layer, to generate spatial data with user-specified resolution.
A common methodology to assess individual absorbed radiation doses and corresponding uncertainties was developed and tested by the dosimetry intercomparison working group (DIWG) for all subjects based on interview data and available exposure data.
