## 6 Quantitative Method to Identify the Potential Technologies to Cover the Future Copernicus Gaps  
In order to identify the potential technologies to cover future gaps over Copernicus infrastructure, a quantitative method has been defined starting from the perspective of the instrument technologies and the variables with gaps. The analysis is centered on the list of the top 10 use cases and 20 variables detected with gaps, and the potential instruments which have been proposed in Table 8. A quantitative method has been applied to rank the technologies suitable to measure the variables with gaps, and identify which technologies cover most of the requirements. The rank order weights used is based on the user requirements, and measurements priorities. A weighting system for the instrument performance parameter has been implemented. First, it defined the numerical score for each instrument capability based on user requirements (Table 9). Then, these numerical scores are evaluated for each measurement with gaps and each factor. In this way, the numerical score for latency is assigned for measurement that required latency time <1 h; for spatial resolution, a high score is assigned for measurement that required spatial resolution <1 km; for the revisit time, a high score for geophysical variables that required <3 h is assigned; for accuracy, a high score for measurements that require accuracy better than the state of the art is assigned. For payload mass and power consumption, the corresponding score for mini and micro platform is assigned; the measurement relevance was assigned taking the following:  
* High relevance measurements: ocean surface currents, wind speed over sea surface, dominant wave direction, and significant wave height measurements. \begin{table}
\begin{tabular}{l||l|l|l} \hline \hline \multirow{2}{*}{**Instrument**} & \multirow{2}{*}{**Measurements**} & \multicolumn{2}{c}{**Requirements [109]**} \\ \cline{3-4}  & & **Accuracy** & **Spatial Resolution** \\ \hline \multirow{6}{*}{**SRAL [10.2]****} & Ocean surface currents & 0.5 m/s & 1-25 km \\ \cline{2-4}  & Significant wave height & 0.1 m & 1-25 km \\ \cline{2-4}  & Dominant wave direction & 10\({}^{\circ}\) & 1-15 km \\ \cline{2-4}  & Sea ice type & 0.25/classes & **Hom** \\ \cline{2-4}  & Sea ice thickness & 1 cm & **1-metmetrical** \\ \cline{2-4}  & Sea ice cover & 5 \% & 12 km-10 m \\ \cline{2-4}  & Wind speed over the sea surface & 1.5 m/s & 1-10 km \\ \cline{2-4}  & Ocean surface currents & 0.5 m/s & 1-25 km \\ \cline{2-4}  & Iceberg tracking & 5\% & **Hom** \\ \cline{2-4}  & Sea ice drift & 1.5 m/s & **Hom** \\ \cline{2-4}  & Sea ice extent & 5\% & 12 km-10 m \\ \cline{2-4}  & Sea ice type & 0.25/classes & **Hom** \\ \cline{2-4}  & **Gband** & Sea ice cover & 5 \% & 12 km-10 m \\ \cline{2-4}  & Dominant wave direction & 10\({}^{\circ}\) & 1-15 km \\ \cline{2-4}  & Significant wave height & 0.1 m & 1-25 km \\ \cline{2-4}  & Sea ice thickness & 1 cm & 1-10 km \\ \cline{2-4}  & Ocean Imagery and water leaving radiance & 5\% & 1 km \\ \cline{2-4}  & Wind speed over the sea surface & 1.5 m/s & 1-10 km \\ \cline{2-4}  & ATLAS [1] & Sea ice thickness & 1-10 km \\ \cline{2-4}  & **VIS \& NIR** & Sea ice thickness & 1-10 km \\ \hline \hline \end{tabular}
\end{table} 
Table 8: _Cont._* Medium relevance measurements: sea ice cover, sea ice type, sea surface temperature, and atmospheric pressure over the sea surface. * Low relevance measurements: Ocean chlorophyll concentration, ocean imagery and weather leaving radiance, CDOM, monitoring system vessels, sea ice extent, sea ice thickness, iceberg tracking, sea ice drift, estimation of crop evapotranspiration, detection of water stress in crops, crop grow and conditions.