Bhubaneswor Dhakal, Salil Bhattarai, Nischal Dhakal
Instruments of meteorological data collection in the mountain are mostly stationed either on hillsides or in valleys. The data cannot well represent the state of climatic changes in transitional agro-ecological belts in the surroundings. Moreover, the human’s stresses experienced from climatic changes are outcomes of interactions of many abiotic and biotic factors, and cannot be well assessed with the instrumental data. The social science-based study is considered a supporting approach to address the instrumental data problem. Previous social science studies consist of many anomalies in research design, data collection, and analysis, intertation. The weaknesses in those studies are primarily caused by a lack of well-developed theoretical models. To address the methodological problem, this study proposed and illustrated “The Random Experience Model”, a pioneer theoretical framework in climate change study. Applicability of the theoretical framework is demonstrated in a pilot study. A few points worth considering in future studies for demonstrating the strengths of the model are listed.