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The Tibetan Plateau (TP) is a global warming hotspot, however, the warming status at high elevation (>5000 m) is poorly understood due to very sparse observations. Here we analyze spatial patterns in TP warming rates based on a novel near-surface air temperature dataset of 1980–2014 recently developed by ingesting high-elevation observations and downscaled reanalysis datasets. We show that the high snow cover persistence at high elevation reduces strengthening of positive feedbacks responsible for elevation dependent warming at low-middle elevations, leading to reversed altitudinal patterns of TP warming above and below 5000 m. An important negative feedback is induced by the presence of snow and glaciers at elevations above 5000 m, due to their “buffering” effects by consuming or reflecting energy that would be used for warming in the absence of snow or ice. A further decrease in snow cover and glacier extent at high elevations may thus amplify the warming on the TP.

Advancements in our understanding of exoplanetary atmospheres, from massive gas giants down to rocky worlds, depend on the constructive challenges between observations and models. We are now on a clear trajectory for improvements in exoplanet observations that will revolutionize our ability to characterize the atmospheric structure, composition, and circulation of these worlds. These improvements stem from significant investments in new missions and facilities, such as JWST and the several planned ground-based extremely large telescopes. However, while exoplanet science currently has a wide range of sophisticated models that can be applied to the tide of forthcoming observations, the trajectory for preparing these models for the upcoming observational challenges is unclear. Thus, our ability to maximize the insights gained from the next generation of observatories is not certain. In many cases, uncertainties in a path towards model advancement stems from insufficiencies in the laboratory data that serve as critical inputs to atmospheric physical and chemical tools. We outline a number of areas where laboratory or ab initio investigations could fill critical gaps in our ability to model exoplanet atmospheric opacities, clouds, and chemistry. Specifically highlighted are needs for: (1) molecular opacity linelists with parameters for a diversity of broadening gases, (2) extended databases for collision-induced absorption and dimer opacities, (3) high spectral resolution opacity data for relevant molecular species, (4) laboratory studies of haze and condensate formation and optical properties, (5) significantly expanded databases of chemical reaction rates, and (6) measurements of gas photo-absorption cross sections at high temperatures. We hope that by meeting these needs, we can make the next two decades of exoplanet science as productive and insightful as the previous two decades. (abr), Comment: This is a white paper originally initiated within NASA's Nexus for Exoplanet System Science (NExSS), with additional community input. Community comment is welcome. Please submit comments and suggestions by going to the Google Doc version of the paper: https://docs.google.com/document/d/1109uy_5n9VWuOOn-huTVv-gJgBFRO9QH0Ojkao1a6Lk/edit?usp=sharing