Synergy of Observations and Models
A synergistic approach combining observations and modeling provides an optimal strategy for answering critical questions regarding how Earth’s climate system has responded to varying levels of greenhouse gases and other forcing factors. Model simulations provide a global picture of the state of the climate system and also a window into how various processes operate to maintain a given climate state. Disparities between simulated climate variables (e.g., surface temperatures, precipitation, ocean circulation) and proxy observations of these state variables pose questions regarding how much of the disparity is due to model biases or deficiencies and how much is due to observational bias. An example of data bias is related to simulated tropical and subtropical SSTs during warm Paleogene climates, which for years were high compared to proxy data. Recent recognition and correction of problems with the proxy data (see Box 4.4) have not brought models and data into greater agreement. An example of model bias is related to simulated high-latitude surface temperatures in warm climate regimes, which have been too low compared to proxy data. Here, continued improvement and development of new innovative observational techniques have strengthened the conclusion that models are challenged to simulate such high polar surface temperatures. This disparity has led to active model exploration of feedback processes that may operate in warm greenhouse climates but are not revealed by data-model studies of Earth’s more recent glacial state. Thus, it is to the benefit of both observational and modeling communities to work in close collaboration through real-time data-model comparison studies. Disparities between models and observations represent synergistic research opportunities.