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Abstract
Low spatial resolution satellite sensors provide information over relatively large targets with typical pixel resolutions of hundreds of km2. However, the spatial scales of ground measurements are usually much smaller. Such differences in spatial scales makes the interpretation of comparisons between quantities derived from low resolution sensors and ground measurements particularly difficult. It also highlights the importance of developing appropriate sampling strategies when designing ground campaigns for validation studies of low resolution sensors.
We make use of statistical modelling of high resolution surface shortwave radiation budget (SSRB) data to look into this problem. A spatial model that describes the SSRB over a selected region is proposed, and the impact of different sampling schemes in the performance of the model is analysed. Both systematic and random sampling schemes can efficiently represent the full observations set.
**Current affiliation: Meteorological Office, Hadley Centre for Climate Prediction and Research, UK
Acknowledgements
This work has been partly funded by the project BFM‐2001‐3286 of the DGCYT (Dirección General de Ciencia y Tecnología). The work of Francisco Montes has also been partly funded by the project GRUPOS03/189 of the Generalitat Valenciana.
Notes
**Current affiliation: Meteorological Office, Hadley Centre for Climate Prediction and Research, UK