In this paper, we present a reliable storage service, called SolarStore, that adaptively trades-off storage reliability versus energy consumption in solar-powered sensor networks. SolarStore adopts a predominantly disconnected network model, where long-running data-collection experiments are conducted in the absence of a continuous connection to the outside world. SolarStore (i) replicates data in the network until the next upload opportunity, and (ii) adapts the degree of data replication dynamically depending on solar energy and storage availability. The goal is to maximize the amount of data that can eventually be retrieved from the network subject to energy and storage constraints. Maximization of retrievable data implies minimizing sensing blackouts due to energy depletion as well as minimizing loss due to node damage in harsh environmental conditions. We have deployed an outdoor solar-powered sensor network, on which SolarStore is implemented and tested. An indoor testbed is also set up for performance evaluation under environmental conditions not attained locally. Experiments show that SolarStore is successful in dynamically responding to variations in the environment in a manner that increases retrievable data under different node failure scenarios.