An emerging body of research about climate change impacts is exploring temperature effects on human activities. However, most studies use simple identification strategies that only explore one or two attributes relating to temperature or to its abnormalities. These simple strategies limit the understanding of temperature effects, and there is debate about the effectiveness of simple identification strategies. To better understand complex temperature effects on human activities, this study uses residential energy consumption as an example and develops identification strategies to capture the temperature effects resulting from temporal patterns (temperature fluctuation), abnormality (temperature departure from normal), and the interdependence among these attributes. For comparison, we use the same data set and model specification as in Deschênes and Greenstone (2011) except for specifications to capture complex temperature effects. We construct variables to capture additional temperature attributes and create the interaction terms among these attributes and temperature levels. Our findings verify the existence of complex temperature effects on energy consumption, and our paper may provoke the discussion of different strategies to better capture climate impacts on human activities.