Estimating inter-node distances based on received radio signal strength (RSSI) is the foundation of RSSI-based outdoor localization in wireless sensor networks (WSNs). However, the accuracy of RSSI-based ranging depends on environmental and weather conditions. Therefore, it is important that RSSI-based ranging adapts to prevailing conditions to improve its range and location accuracy. This paper analyzes and evaluates RSSI-based ranging and adaptive techniques in outdoor WSNs to improve the range quality. The findings highlight the effects of path loss exponent (PLE) estimation error and temperature change on RSSI-based ranging. Consequently, we analyze techniques for mitigating these detrimental effects and propose an adaptive RSSI-based ranging algorithm in order to improve the ranging quality in changing outdoor conditions. The algorithm comprises link RSSI estimation, temperature compensation, PLE estimation, and inter-node distance estimation. Furthermore, we evaluate the performance of the proposed algorithm and compare different WSN-specific PLE estimation techniques by employing real measurement data of 2.4 GHz IEEE 802.15.4-compliant WSN nodes. The results indicate that although ranging error can be mitigated using the proposed adaptive techniques, the accuracy when a single PLE estimate is used is, in general, limited due to high inter-link PLE variation.