Through automated negotiation we aim to improve task allocation in a distributed sensor network. In particular, we look at a type of adaptive weather-sensing radar that permits the radar to focus its scanning on certain regions of the atmosphere. Current control systems can only computationally handle the decision making for a small number of radars because of the complexity of the process. One solution is to partition the radars into smaller, independent sets. Redundant scanning of tasks and loss of cooperative scanning capabilities can occur as a result. With negotiation we can reduce these occurrences, helping to ensure that the correct radars scan tasks based on the overall social welfare. We develop a distributed negotiation model where on each cycle the overall system utility improves or remains constant. Experimental results show that as compared to the centralized task allocation mechanism, the proposed distributed task allocation mechanism achieves almost the same level of social welfare but with a significantly reduced computational load.