Accurate and reliable information about the spatial variation of the radio propagation delay due to the ionosphere (ionospheric gradient) is an important parameter in both high precision and high integrity GNSS augmentation systems. Reliable monitoring and modelling of the ionospheric gradient variation during anomalous ionospheric events remains a challenging research topic. It requires understanding of the local phenomena and knowledge of the traveling ionospheric disturbance key characteristics including spatial scale size, orientation, and propagation velocity. This article presents results from a two year long monitoring campaign carried out in 2021-2022 in Northern Norway, where a cluster of thirteen receivers centered at 69.5° N, 19° E was used to study the spatial variation of the ionospheric delay on a multi-scale network (baseline lengths between 1.35–75 km). Data captured by this receiver cluster was analyzed for the presence of ionospheric gradients between stations, with each of the detected events characterized in terms of the front slope, width and propagation velocity. This analysis is complemented by observations made using the same receiver cluster during an intense geomagnetic storm that took place on 10-12 May 2024. The key conclusions of this study are that ionospheric gradient events seen in this region are spatially small-scale irregularities with estimated widths of 60 km or less ranging from quasi static to moving at velocities of 2000 m/s. Nearly all observed ionospheric front slope values were under 150 mm/km. Gradient observations made during the geomagnetic storm were almost always accompanied by scintillation. Spatially small-scale irregularities can be difficult to observe with large scale networks as the isolated regions of disturbance can pass undetected between station pairs. This might pose challenges to systems/services where interpolation of the atmospheric residuals is done based on observations from a larger scale network/cluster, or concepts using a set of monitoring stations at longer baselines to assist real-time ionospheric gradient threat monitoring and detection.